82 pubblicazioni classificate nel seguente modo:

Combining an LNS-based approach and organizational mining for the Resource Replacement Problem
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Diamantini, Claudia; Pisacane, Ornella; Potena, Domenico; Storti, Emanuele
Classificazione: 1 Contributo su Rivista
Abstract: For companies, it is crucial to promptly react to (even short-term) lack of resources, for guaranteeing the continuity of the operations in business processes. This leads to the solution of a Resource Replacement Problem (RRP) aimed at reassigning as many activities performed by resources that are no longer available to those that are available. To this purpose, several aspects are considered simultaneously, e.g., resources skills, workloads and other domain-specific constraints. In this paper, we propose an innovative hybrid approach for solving RRP, combining mathematical optimization with organizational mining. In particular, logs of past process executions are used to model a social network of resources by organizational mining techniques. Then, a similarity measure among resources is derived and exploited along with run-time resource workload and information on activities priority to formulate an Integer Linear Programming (ILP) model for reassigning the activities of unavailable resources, minimizing the total reassignment cost. To efficiently solve RRP, a Large Neighborhood Search based matheuristic is developed. Computational experiments show that the proposed matheuristic outperforms the commercial solver used to solve the ILP model. A sensitivity analysis, on possible variations of the input parameters and on the moves of the matheuristic, concludes the work.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/322991

A matheuristic for the electric vehicle routing problem with time windows and a realistic energy consumption model
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Bruglieri, Maurizio; Paolucci, Massimo; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: We address an Electric Vehicle Routing Problem with Time Windows (E-VRPTW) considering several real-like factors in the energy consumption model, e.g., the payload and the vehicle speed. We model E-VRPTW as a Mixed Integer Linear Program (MILP) where the speeds of vehicles are continuous variables that can vary between a minimum and a maximum value. Moreover, the proposed MILP formulation is cloneless since it allows using more than once the same recharging station without introducing dummy copies of it. To efficiently solve large-sized instances of the problem, we design a Random Kernel Search (RKS) matheuristic approach, based on the cloneless MILP formulation, that in turn exploits another matheuristic, called Random k-Degree Search (RkDS), to generate an initial feasible solution. We compare the results produced by a MILP solver using the MILP formulation with the ones obtained by the RKS on instances up to 100 customers derived from the benchmark instances of E-VRPTW. We show that the proposed matheuristic outperforms the cloneless MILP formulation on the medium/large-sized instances and also that it is robust, being not significantly sensitive to the values of the parameters used by the RkDS to generate the initial solution and to the initial time limit for the restricted MILP models.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/315015

A survey on emergent trends in the optimization of car-sharing systems
INTERNATIONAL TRANSACTIONS IN OPERATIONAL RESEARCH
Autore/i: Bruglieri, M.; Pisacane, O.
Classificazione: 1 Contributo su Rivista
Abstract: This paper reviews the most recent literature on the optimization of car-sharing systems. Unlike other surveys, we do not focus on a single aspect of car-sharing systems, but we consider a wide range of optimization problems with a global view. Our aim is threefold. First, we revise the classic decision problems arising in car-sharing systems with conventional and electric vehicles, such as the fleet size, the station location, and the vehicle relocation. Then, we discuss some of the most recent decision problems arising in more innovative car-sharing systems, like those with autonomous vehicles, with mixed fleets, and the multi-modal and the time-dependent ones. Finally, we focus on new perspectives arising in the optimization of some innovative car-sharing services that are not yet (or little) investigated in the literature and that are worthy of attention from the operations research point of view. For each of them, we also highlight new and challenging open decision problems that deserve academic attention
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/315428

Optimization approaches for the Mixed Fleet Vehicle Routing Problem with Congestion Charge Zones
8th meeting of the EURO Working Group on Vehicle Routing and Logistics Optimization (VeRoLog)
Autore/i: Bruglieri, Maurizio; Çatay, Bülent; Keskin, Merve; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/302008

Optimizing a real-time carpooling service
International Conference on Optimization and Decision Science (ODS 2022)
Autore/i: Bruglieri, Maurizio; Peruzzini, Roberto; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/302009

A matheuristic approach for effciently routing a fleet of electric vehicles under a realistic energy consumption model
8th meeting of the EURO Working Group on Vehicle Routing and Logistics Optimization (VeRoLog)
Autore/i: Bruglieri, Maurizio; Paolucci, Massimo; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/302004

The Effect of Low Emission Zones on the Routing of Electric and Fossil-Fuel Vehicles
International Conference on Optimization and Decision Science (ODS 2022)
Autore/i: Bruglieri, Maurizio; Çatay, Bülent; Keskin, Merve; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/302006

A GRASP with penalty objective function for the Green Vehicle Routing Problem with Private Capacitated Stations
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Bruglieri, M; Ferone, D; Festa, P; Pisacane, O
Classificazione: 1 Contributo su Rivista
Abstract: Due to the recent worries about the environment, the transportation companies are incentivized to use Alternative Fuel Vehicles (AFVs) instead of the conventional ones. However, due to the limited AFV driving range and since the Alternative Fuel Stations (AFSs) are usually not widespread on the territory, the routes of AFVs have to be properly planned in order to prevent them from remaining without the sufficient fuel to reach the depot or the closest station. The Green Vehicle Routing Problem (G-VRP) aims at determining the AFVs routes, each one serving customers within a maximum duration, minimizing the total travel distance and, if necessary, including stops at AFSs. Contrary to G-VRP, G-VRP with Capacitated AFSs (G-VRP-CAFS) more realistically assumes that each AFS has a limited number of fueling pumps and therefore prevents overlapping in refueling operations. In this paper, we propose a Greedy Randomized Adaptive Search Procedure (GRASP), which properly uses some theoretical results and efficiently solves large-sized instances of G-VRP-CAFS. Computational results carried out on both benchmark instances and large-sized instances show the effectiveness and the efficiency of the proposed GRASP.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/297309

Comparing data-driven meta-heuristics for the bi-objective Component Repairing Problem
2022 IEEE Intl Conf on Dependable, Autonomic and Secure Computing, Intl Conf on Pervasive Intelligence and Computing, Intl Conf on Cloud and Big Data Computing, Intl Conf on Cyber Science and Technology Congress (DASC/PiCom/CBDCom/CyberSciTech)
Autore/i: Diamantini, Claudia; Mircoli, Alex; Pisacane, Ornella; Potena, Domenico
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Due to both the increasing use of automation in production processes and the budget devoted for purchasing equipment, maintenance plays a key role in making a company competitive in the marketplace. Moreover, the use of data analysis techniques and the advent of Internet of Things make the IoT-based predictive maintenance possible. In addition, since all the resources (e.g., budget and human) involved in the maintenance activities are usually limited, a company is also interested in defining optimized maintenance plans. In this paper, the integration of IoT-based predictive maintenance with optimization techniques is investigated by developing a data-driven Greedy Randomized Adaptive Search Procedure (GRASP) meta-heuristic aimed at efficiently defining maintenance plans. In particular, we address the bi-objective component repairing problem (b-CRP), aimed at determining the set of components of a production system to repair that are more likely to fail. Having the breakage probability of each component, derived from historical data, the system reliability is maximized and the maximum time required to repair one component among those selected in the solution is minimized, under constraints on both budget and time for performing the maintenance activities. Then, we compare the solutions of GRASP with those of an already existing bi-objective Large Neighborhood Search meta-heuristic.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/309061

The VRP with Mixed Fleet of Electric and Traditional Vehicles and Congestion Charge Zones
50th International Conference on Optimization and Decision Science- Optimization in Artificial Intelligence and Data Science
Autore/i: Pisacane, Ornella; Bruglieri, Maurizio; Çatay, Bulent; Keskin, Merve; Mancini, Simona
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/319911

Comparing matheuristic approaches for the Electric Vehicle Routing Problem with Time Windows
50th International Conference on Optimization and Decision Science- Optimization in Artificial Intelligence and Data Science
Autore/i: Paolucci, Massimo; Bruglieri, Maurizio; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/319912

A GRASP with penalty objective function for the Green Vehicle Routing Problem with Capacitated Fuel Stations
50th International Conference on Optimization and Decision Science- Optimization in Artificial Intelligence and Data Science
Autore/i: Bruglieri, Maurizio; Ferone, Daniele; Festa, Paola; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/319913

Routing a Mixed Fleet of Electric and Traditional Vehicles with Congestion Charge Areas
31st European Conference on Operational Research
Autore/i: Bruglieri, Maurizio; Çatay, Bülent; Keskin, Merve; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291097

Near Optimal Solutions for the Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations
31st European Conference on Operational Research
Autore/i: Pisacane, Ornella; Bruglieri, Maurizio; Ferone, Daniele; Festa, Paola
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/291098

A more efficient cutting planes approach for the green vehicle routing problem with capacitated alternative fuel stations
OPTIMIZATION LETTERS
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: The Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations assumes that, at each station, the number of vehicles simultaneously refueling cannot exceed the number of available pumps. The state-of-the-art solution method, based on the generation of all feasible non-dominated paths, performs well only with up to 2 pumps. In fact, it needs cloning the paths between every pair of pumps. To overcome this issue, in this paper, we propose new path-based MILP models without cloning paths, for both the scenario with private stations (i.e., owned by the fleet manager) and that with public stations. Then, a more efficient cutting plane approach is designed for addressing both the scenarios. Numerical results, obtained considering a set of benchmark instances ad hoc generated for this work, show both the efficiency and the effectiveness of this new cutting plane approach proposed. Finally, a sensitivity analysis, carried out by varying the number of customers to be served and their distribution, shows very good performances of the proposed approach
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/288323

The Multi-period Multi-trip Container Drayage Problem with Release and Due Dates
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Bruglieri, M.; Mancini, S.; Peruzzini, R.; Pisacane, O.
Classificazione: 1 Contributo su Rivista
Abstract: The Container Drayage Problem (CDP) aims at routing a fleet of trucks, based at a common terminal, to serve customers while minimizing the total travel distance. Each trip starts from and ends at the terminal, and handles a subset of customers. Each customer requires either that a container is picked up or delivered. We introduce a more realistic variant, i.e., the Multi-trip Multi-period CDP with Release and Due Dates (MM-CDP-RDD), in which the planning horizon is composed of several periods (days). On each day, each truck may perform more than one trip respecting the Release and Due Dates (RDD) associated with customer services, corresponding to the first and the last day on which the service can be carried out, respectively. Drivers’ contracts impose limitations on the maximum driving time allowed on each day, on two consecutive days and on the whole weekly planning horizon. To model the MM-CDP-RDD, we propose both an Arc-based Integer Linear Programming (ILP) formulation and a Trip-based ILP formulation that receives as input all the feasible non-dominated trips. To efficiently address medium/large-sized instances of the problem, we also design six Combinatorial Benders’ Cuts approaches. All the methods are compared on a rich set of instances generated for this new problem.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283919

Data-driven predictive maintenance policy based on multi-objective optimization approaches for the component repairing problem
ENGINEERING OPTIMIZATION
Autore/i: Pisacane, Ornella; Potena, Domenico; Antomarioni, Sara; Bevilacqua, Maurizio; Emanuele Ciarapica, Filippo; Diamantini, Claudia
Classificazione: 1 Contributo su Rivista
Abstract: In systems with many components that are required to be constantly active, such as refineries, predicting the components that will break in a time interval after a stoppage may significantly increase their reliability. However, predicting the set of components to be repaired is a challenging task, especially when several conditions (e.g. breakage probability, repair time and cost) have to be considered simultaneously. A data-driven predictive maintenance policy is proposed for maximizing the system reliability and minimizing the maximum repair time, considering both budget and human resources constraints. Therefore, a data-driven algorithm is designed for extracting component breakage probabilities. Then, two bi-objective optimization approaches are proposed for determining the set of components to repair. The former is based on the formulation of a bi-objective mixed integer linear programming model solved through the AUGMEnted ε-CONstraint (AUGMECON) method. The latter implements a bi-objective large neighbourhood search, outperforming the first approach.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/284711

Efficient solutions for the Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations
18th Cologne-Twente Workshop on Graphs and Combinatorial Optimization
Autore/i: Bruglieri, M.; Ferone, D.; Festa, P.; Pisacane, O.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this paper, we propose a metaheuristic approach for efficiently solving the Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations (G-VRP-CAFS). The G-VRP-CAFS, a variant of the traditional G-VRP, aims at routing a fleet of Alternative Fuel Vehicles (AFVs), based at a common depot, in order to serve a set of customers, minimizing the total travel distance. Due to the limited autonomy of the AFVs, some stops at Alternative Fuel Stations (AFSs) may be necessary during each trip. Unlike the G-VRP, in the G-VRP-CAFS, the AFS capacity, in terms of fueling pumps that are simultaneously available, is realistically assumed limited. For such a problem, we design an Iterated Local Search algorithm, in order to obtain good quality solutions in reasonable amount of time also on real-life alike case studies. Preliminary results, carried out on a set of benchmark instances taken from the literature, are promising.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/283909

MILP formulations and Cutting Plane approaches for the Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations
Workshop of the EURO Working Group on Vehicle Routing and Logistics optimization (VeRoLog)
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269363

More efficient formulations and valid inequalities for the Green Vehicle Routing Problem
TRANSPORTATION RESEARCH. PART C, EMERGING TECHNOLOGIES
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: The Green Vehicle Routing Problem (G-VRP) aims to efficiently route a fleet of Alternative Fuel Vehicles, based at a common depot, in order to serve a set of customers, minimizing the total travel distance. Because of the limited driving range of these vehicles, intermediate stops at the Alternative Fuel Stations must also be considered. For the G-VRP, we propose two Mixed Integer Linear Programming formulations allowing multiple visits to the stations without introducing dummy copies of them. In the first model, only one visit to a station between two customers or between a customer and the depot is allowed. While, in the second model, two consecutive visits to stations are also permitted. In addition, the two formulations are strengthened through both dominance criteria to a priori identify the stations that are more efficient to use in each route and valid inequalities, specifically tailored for the G-VRP. Computational results, carried out on benchmark instances, show that our formulations strongly outperform the exact solution approaches presented in the literature. Finally, in order to better investigate the issue of the consecutive refueling stops, a new set of instances is properly generated and significant transport insights are also provided.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/267096

A predictive association rule-based maintenance policy to minimize the probability of breakages: application to an oil refinery
INTERNATIONAL JOURNAL, ADVANCED MANUFACTURING TECHNOLOGY
Autore/i: Antomarioni, Sara; Pisacane, Ornella; Potena, Domenico; Bevilacqua, Maurizio; Ciarapica, Filippo Emanuele; Diamantini, Claudia
Classificazione: 1 Contributo su Rivista
Abstract: Effective maintenance policies can support companies to deal with process interruptions and consequently, to prevent significant profit losses. Moreover, the proliferation of structured and unstructured data due to production plants validates the application of knowledge discovery in databases techniques to increase processes’ reliability. In this paper, an innovative maintenance policy is proposed. It aims at both predicting components breakages through association rule mining and determining the optimal set of components to repair in order to improve the overall plant’s reliability, under time and budget constraints. An experimental campaign is carried out on a real-life case study concerning an oil refinery plant. Finally, numerical results are discussed considering different blockage categories and number of components and by varying some significant input parameters.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/266285

A Graph-Based Analysis on the Growth and Migration of MDA-MB-231 Breast Cancer Cells
International Conference on Optimization and Decision Science, XLIX annual meeting organized by the Italian Operations Research Society
Autore/i: Bracci, Massimo; Marinelli, Fabrizio; Pisacane, Ornella; Pizzuti, Andrea
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Cells migration as well as their growth are due to several interactions, e.g., with either other (close) cells or the micro-environment. The analysis of both such phenomena plays a key role especially during the tissue formation/regeneration and in tumorigenesis and, in many cases, can also give a significant support to cancer pharmacogenomic studies. We focus attention on the analysis of both growth and migration of the MDAMB-231 breast cancer cells, since the breast cancer is actually registering the highest mortality of any cancer in women worldwide. More specifically, we aim at analyzing the changes of the same breast tissue for increasing hour intervals. For this purpose, we propose optimization-based approaches to support such an analysis by studying the images of in vitro human breast cells produced in different time instants by a microscope with 25x magnification. Firstly, each image is converted into a proper cell-graph. Then, in order to evaluate the similarity among two cell-graphs, each related to an image of the same tissue in a different instant of time, a Maximum Common Edge Subgraph Problem (MCESP) is solved. We model the MCESP through Integer Linear Programming (ILP) and, in order to efficiently address realistic instances, we also design a Tabu Search meta-heuristic. Moreover, a hybrid solution approach combining the Tabu Search with ILP is also proposed. Preliminary numerical results, carried out on both a set of benchmark instances and a set of realistic case studies, show the promising performances of our approaches compared to those of the literature.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269542

The Green Vehicle Routing Problem with Reserved Capacitated
International Conference on Optimization and Decision Science, XLIX annual meeting organized by the Italian Operations Research Society
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Green Vehicle Routing Problem (G-VRP) aims at routing Alternative Fuel Vehicles (AFVs), based at a common depot, for serving a set of customers. Each route starts and ends from/at the depot, serving a subset of customers. Due to its limited driving range, an AFV may stop at Alternative Fuel Stations (AFSs) along its route. While in the literature the AFS capacity is assumed unlimited, we address the extension of the G-VRP with Capacitated AFSs where at most η AFVs can be simultaneously refueled at an AFS with η fueling pumps. We model it by both Arc and Path based Mixed Integer Linear Programming. The latter model (P-MILP) considers only feasible nondominated paths. We also design two efficient slightly different P-MILP based Cutting Planes methods where in the relaxations, the AFS capacity constraints are dropped. Moreover, at each iteration, in the former, a cut is added for restoring the capacity constraint violated by the current solution while, in the latter, a set of cuts are included for restoring the capacity constraints that may be luckily violated later. For preventing possible queues at AFSs, the possibility of reserving them is considered. Then, our approaches are extended introducing time windows at AFSs for modelling their availability. Results, on both benchmark and realistic instances, are compared in scenarios with and without AFS reservation.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269539

The green vehicle routing problem with capacitated alternative fuel stations
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: In this paper, we introduce the Green Vehicle Routing Problem with capacitated Alternative Fuel Stations (AFSs), a more realistic variant of the Green Vehicle Routing Problem where the capacity of the AFSs is addressed. Two Mixed Integer Linear Programming formulations, one based on arc-variables and one on path-variables are presented. In order to reduce the computational time required to solve the problem, two variants of an exact cutting planes method are proposed. All the proposed approaches are also extended to be applied in a scenario in which AFSs reservation is allowed, by introducing time windows at them. Computational experiments are carried out on both benchmark and challenging realistic instances for which the capacity of the AFSs is a crucial issue
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269287

The Multi-period Multi-trip Containers Drayage Problem with Due and Release Dates
Workshop of the EURO Working Group on Vehicle Routing and Logistics optimization (VeRoLog)
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Peruzzini, Roberto; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269362

A Path-based solution approach for the Green Vehicle Routing Problem
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: The Green Vehicle Routing Problem concerns routing alternative fuel vehicles, based at a single depot, to handle a subset of customers while minimizing the total travel distance. Due to limited fuel autonomy, each vehicle may need to stop at Alternative Fuel Stations (AFSs) during its trip. We propose a two-phase solution approach in which a route is seen as the composition of paths, each one handling a subset of customers without intermediate stops at AFSs. In the first phase, all feasible paths are generated limiting their number through dominance rules. In the second phase, the paths are selected and properly combined to generate the routes via Mixed Integer Linear Programming. Our approach, tested on small- to medium-sized benchmark instances, outperforms the existing exact methods obtaining always the optimal solution in a smaller average computational time. Furthermore, the approach was converted into a heuristic one considering in the first phase only a subset of feasible non-dominated paths. In this way, we can also address larger- sized instances outperforming, in terms of solution quality, the best heuristic approach in the literature.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/261980

Collaborative energy management in a micro-grid by multi-objective mathematical programming
ENERGY AND BUILDINGS
Autore/i: Pisacane, Ornella; Severini, Marco; Fagiani, Marco; Squartini, Stefano
Classificazione: 1 Contributo su Rivista
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269640

The Collaborative Relocation in One-Way Electric Carsharing Systems
International Conference on Optimization and Decision Science, XLIX annual meeting organized by the Italian Operations Research Society
Autore/i: Bruglieri, Maurizio; Marinelli, Fabrizio; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In Vehicle Sharing Systems (VSSs), users can rent a vehicle paying a charge depending only on the actual time of use. In one-way VSSs, they are also allowed to delivery a vehicle to a station that may be different from the one of pick-up. This of course introduces flexibility but also poses the problem of re-balancing the demand and the supply of vehicles between the stations by means of operators. We address the Electric Vehicles Relocation Problem (EVReP) assuming that the operators directly drive vehicles (indeed cars in our application) from a station of pick-up to one of delivery, moving by folding bicycles from a station of delivery to one of pick-up, as in Bruglieri et al. (2014) and Bruglieri et al. (2017). Collaboration among operators is also possible through the ”carpooling”, i.e., an operator can give a lift to the others moving from a station of pick-up to one of delivery. We study the economic sustainability of the collaborative EVReP through a Mixed Integer Linear Programming (MILP) formulation assuming that a revenue is associated with each relocation request satisfied and an hourly cost with the operators used. The MILP allows routing and scheduling the operators with the objective of maximizing the total profit, i.e., the difference between the total satisfied request revenue and the total operator cost. The constraints allow satisfying the requests within their time windows and taking into account the limited EV battery autonomy. Through numerical experiments on real like instances, we show that the collaboration among operators can improve the total profit of the carsharing system. Moreover, the new MILP formulation outperforms the previous ones also in terms of computational time being based on two-indices variables by elimination of their dependency on the relocation operators.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/269540

From Artificial Intelligence and Databases to Cognitive Computing: Past and Future Computer Engineering Research at UNIVPM
The First Outstanding 50 Years of “Università Politecnica delle Marche”
Autore/i: Cucchiarelli, Alessandro; Diamantini, Claudia; Dragoni, Aldo Franco; Francescangeli, Fabrizio; Frontoni, Emanuele; Mancini, Adriano; Marinelli, Fabrizio; Morbidoni, Christian; Pezzella, Ferdinando; Pisacane, Ornella; Potena, Domenico; Ribighini, Giuseppa; Spalazzi, Luca; Storti, Emanuele; Ursino, Domenico; Vici, Francesco; Zingaretti, Primo
Editore: Springer, Cham
Classificazione: 2 Contributo in Volume
Abstract: In the last decades, Computer Engineering has shown an impressive development and has become a pervasive protagonist in daily life and scientific research. Databases and Artificial Intelligence represent two of the major players in this development. Today, they are quickly converging towards a new, much more sophisticated and inclusive, paradigm, namely Cognitive Computing. This paradigm leverages Big Data and Artificial Intelligence to design approaches and build systems capable of (at least partially) reproducing human brain behavior. In this paradigm, an important role can be also played by Mathematical Programming. Cognitive systems are able to autonomously learn, reason, understand and process a huge amount of extremely varied data. Their ultimate goal is the capability of interacting naturally with their users. In the last 50 years, UNIVPM has played a leading role in scientific research in Databases and Artificial Intelligence, and, thanks to the acquired expertise, is going to play a key role in Cognitive Computing research in the future.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/272654

The Electric Vehicle Relocation Problem in Carsharing Systems with Collaborative Operators
Proceedings of 16th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2018)
Autore/i: Bruglieri, Maurizio; Marinelli, Fabrizio; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: We address the problem of balancing the demand and the availability of vehicles between stations in urban one-way electric carsharing systems through operator relocations. Unlike the previous papers, we assume that the operators can collaborate among them through the carpooling, i.e., giving a lift to the others when moving an EV from a pick-up request station to one of delivery. For this new problem, we propose a Mixed Integer Linear Programming formulation and a column generation based heuristic solution approach.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258944

Solving the Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations
Proceedings of 16th Cologne-Twente Workshop on Graphs and Combinatorial Optimization (CTW 2018)
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Green Vehicle Routing Problem (GVRP) aims to efficiently route a fleet of Alternative Fuel Vehicles (AFVs), in order to serve a set of customers, minimizing the total travel distance. Each AFV leaves from a common depot, serves a subset of customers and returns to the depot, without exceeding a maximum duration. Due to their limited driving range, the AFVs may need to refuel one or more times at the Alternative Fuel Stations (AFSs), along their route. In this work, we introduce the GVRP with Capacitated AFSs (GVRP-CAFS) in which only a limited number of AFVs can refuel at the same time at each AFS to account for their limited capacity. In order to solve the GVRP-CAFS, we propose an exact approach in which a route is the composition of paths, each handling a subset of customers without intermediate stops at AFSs. Firstly, all feasible non-dominated paths are generated. Secondly, via a path-based Mixed Integer Programming model, the paths are selected and properly combined each other to generate the routes of the optimal GVRP-CAFS solution. To reduce the computational times, a relaxed version of the path-based model is solved and then, the violated constraints are iteratively added. Some preliminary results are also discussed.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258942

An exact approach for routing a fleet of green vehicles with capacitated fuel stations
Book of Abstracts of 29th European Conference on Operational Research (EURO2018)
Autore/i: Mancini, S.; Bruglieri, M.; Pisacane, O.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259388

An Adaptive Large Neighborhood Search for Relocating Vehicles in Electric Carsharing Services
DISCRETE APPLIED MATHEMATICS
Autore/i: Bruglieri, M.; Pezzella, F.; Pisacane, O.
Classificazione: 1 Contributo su Rivista
Abstract: We propose an Adaptive Large Neighborhood Search metaheuristic to solve a vehicle relocation problem arising in the management of electric carsharing systems. The solution approach, aimed to optimize the total prot, is tested on three real-like benchmark sets of instances. It is compared with a Tabu Search, ad hoc designed for this work, with a previous Ruin and Recreate metaheuristic and with the optimal results obtained via Mixed Integer Linear Programming. We also develop a bounding procedure to evaluate the solution quality when the optimal solution is not available.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/256998

A Combinatorial Benders' Cuts based Exact Method for the Multi Trip Containers Drayage Problem
Book of Extended Abstracts of ODYSSEUS 2018-Seventh International Workshop on Freight Transportation and Logistics
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258937

Optimizing vehicle relocations in one-way electric carsharing systems
Book of Abstracts of 29th European Conference on Operational Research (EURO2018)
Autore/i: Bruglieri, M; Marinelli, F.; Pisacane, O.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259387

A two-phase optimization method for a multiobjective vehicle relocation problem in electric carsharing systems
JOURNAL OF COMBINATORIAL OPTIMIZATION
Autore/i: Bruglieri, Maurizio; Pezzella, Ferdinando; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: The paper focuses on one-way electric carsharing systems, where the fleet of cars is made up of Electric Vehicles (EVs) and the users can pick-up the EV at a station and return it to a different one. Such systems require efficient vehicle relocation for constantly balancing the availability of EVs among stations. In this work, the EVs are relocated by workers, and the issue of finding a trade-off among the customers’ satisfaction, the workers’ workload balance and the carsharing provider’s objective is addressed. This leads to a three-objective optimization problem for which a two-phase solution approach is proposed. In the first phase, feasible routes and schedules for relocating EVs are generated by different randomized search heuristics; in the second phase, non-dominated solutions are found through epsilon-constraint programming. Computational results are performed on benchmark instances and new large size instances based on the city of Milan.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/258366

Collaborative Energy Management in Micro-Grid environments through multi-objective optimization
Proceedings of IJCNN2018
Autore/i: Severini, Marco; Pisacane, Ornella; Fagiani, Marco; Squartini, Stefano
Editore: Institute of Electrical and Electronics Engineers Inc.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In this work, we propose a multi-objective Mixed Integer Linear Programming formulation for addressing the Collaborative Energy Management Problem with the aim of maximizing the net profit of both the Building Manager and all the apartments. The planning horizon is discretized into a finite set of periods, i.e., time intervals. In this way, both the residents’ tasks and the storage activity can be scheduled over the time horizon. The decision variables take into account both the energy resources shared among the apartments, i.e., the ones administrated by the Building Manager, and the local energy resources of each apartment. Together with the traditional scheduling constraints, we also impose both time windows and priority conditions. In particular, regarding the former, each task can be scheduled starting from a specific period. While, according to the latter, each task has a list of prior tasks, of the same resident, that have to be scheduled before it. The proposed formulation is evaluated by investigating the management of a block of four apartments. In one scenario, the apartments are considered as independent entities. In the other one, a collaborative management is performed. The performance comparison reveals that the collaborative management can improve the energy sale revenue up to 26%, providing additional profit to be shared among the apartment owners and the Building Manager.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/259204

A path-based Mixed Integer Linear Programming formulation for the Green Vehicle Routing Problem
Book of Abstracts of The sixth meeting of the EURO Working Group on Vehicle Routing and Logistics optimization
Autore/i: Pisacane, Ornella; Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Green Vehicle Routing Problem (G-VRP) is a variant of the classical Vehicle Routing Problem (VRP) in which Green Vehicles (GVs), such as those with alternative fuel propulsion, are considered. Since GVs are characterized by a limited driving range, one or more stops at Refueling Stations (RSs) may be required along their trip. The goal of the problem is to serve a set of customers exploiting a fleet of identical GVs and minimizing their total travelled distance. Each vehicle leaves from the depot and returns to it. A maximum limit is imposed on the route duration. We propose a path-based Mixed Integer Linear Programming formulation for the G-VRP. In classical VRPs, paths enumeration techniques cannot be adopted due to the exponential number of feasible paths. On the contrary, in the G-VRP, given the GV autonomy constraints, the number of feasible paths is somehow limited. We generate all the feasible paths between the depot and each RS and between two RSs. We also introduce some rules to a priori exclude dominated paths from the feasible set. Such a feasible set is given in input to a Set-Partitioning formulation with the aim of selecting a subset of paths that, properly combined, compose the solution routes for the G-VRP. Computational results, carried out on benchmark instances, show that our approach is much faster than every exact method already presented in the literature, and it is also suitable to detect the optimal solutions in almost all the test cases.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253693

The Green Vehicle Routing Problem with Capacitated Alternative Fuel Stations
Book of Abstracts of The sixth meeting of the EURO Working Group on Vehicle Routing and Logistics optimization
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This work addresses the problem of efficiently routing a set of Alternative Fuel Vehicles (AFVs), considering that, during their trips, some stops at Alternative Fuel Stations (AFSs) have to be planned. Every AFV leaves from a common depot and returns to it, after serving a subset of customers. Due to some forms of contract with the drivers, an upper bound is usually imposed on the duration of each route. The aim is to dene the optimal routing of the AFVs in order to minimize the total traveled distance. This problem is known in the literature as the Green Vehicle Routing Problem (G-VRP). Several Mixed Integer Linear Programming (MILP) formulations have been already presented to model it. The G-VRP assumes that an unlimited number of vehicles may be simultaneously refueled at the same AFS. This hypothesis is not realistic, since AFSs typically have a very small number of refueling locations. To manage this issue, we propose an extension of the G-VRP that models the more realistic situation where a capacity is associated with every AFS, bounding the number of vehicles that can simultaneously refuel. The capacity constraint makes more challenging the scheduling of the stops at the AFSs, since now the AFSs become a shared resource of the problem. For this new version of the GVRP, we propose a MILP formulation and a heuristic approach. Preliminary numerical results have been carried out on some benchmark instances, properly adapted to this extension of the G-VRP.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253694

An Adaptive Large Neighborhood Search for Relocating Vehicles in Electric Carsharing Services
Metaheuristics: Proceeding of the MIC and MAEB 2017 Conferences
Autore/i: Bruglieri, Maurizio; Pezzella, Ferdinando; Pisacane, Ornella
Editore: Universitat Pompeu Fabra
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: We propose an Adaptive Large Neighborhood Search metaheuristic to solve a vehicle relocation problem arising in the management of electric carsharing systems. The solution approach, aimed to optimize the total profit, is tested on two real-like benchmark sets of instances and compared with both a previous Ruin and Recreate metaheuristic and the optimal results obtained through a Mixed Integer Linear Programming formulation, when available
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253692

A three-phase matheuristic for the time-effective electric vehicle routing problem with partial recharges
ELECTRONIC NOTES IN DISCRETE MATHEMATICS
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella; Suraci, Stefano
Classificazione: 1 Contributo su Rivista
Abstract: We propose a three-phase matheuristic, combining an exact method with a Variable Neighborhood Search local Branching (VNSB) to route a fleet of Electric Vehicles (EVs). EVs are allowed stopping at the recharging stations along their routes to (also partially) recharge their batteries. We hierarchically minimize the number of EVs used and the total time spent by the EVs, i.e., travel times, charging times and waiting times (due to the customer time windows). The first two phases are based on Mixed Integer Linear Programs to generate feasible solutions, used in a VNSB algorithm. Numerical results on benchmark instances show that the proposed approach finds good quality solutions in reasonable amount of time.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/247420

Heuristic algorithms for the operator-based relocation problem in one-way electric carsharing systems
DISCRETE OPTIMIZATION
Autore/i: Bruglieri, Maurizio; Pezzella, Ferdinando; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: This paper addresses an Electric Vehicle Relocation Problem (E-VReP), in one-way carsharing systems, based on operators who use folding bicycles to facilitate vehicle relocation. In order to calculate the economic sustainability of this relocation approach, a revenue associated with each relocation request satisfied and a cost associated with each operator used are introduced. The new optimization objective maximizes the total profit. To overcome the drawback of the high CPU time required by the Mixed Integer Linear Programming formulation of the E-VReP, two heuristic algorithms, based on the general properties of the feasible solutions, are designed. Their effectiveness is tested on two sets of realistic instances. In the first, all the requests have the same revenue, while, in the second, the revenue of each request has a variable component related to the user's rent-time and a fixed part related to customer satisfaction. Finally, a sensitivity analysis is carried out on both the number of requests and the fixed revenue component.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245664

On the Green Vehicle Routing Problem
Book of Abstract 46th Annual Conference of the Italian Operational Research Society
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella
Luogo di pubblicazione: Tireste
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The road transport impacts signicantly on the worsening of the air pollution as highlighted by recent studies. The use of Alternative Fuel Vehicles (AFVs) contributes to the reduction of the harmful emissions but it is currently limited by the short driving range so that an AFV may require many refuels in a trip. In addition, the poor availability of the Alternative Fuel Stations (AFSs) on the networks limits the usage of AFVs also in urban contexts. Therefore, the problem of efficiently routing the AFVs to provide eco-sustainable transport solutions arises. It is not new to the Operations Research community and it was introduced in the literature by [1] as the Green Vehicle Routing Problem (G-VRP). The G-VRP deals with the planning of the routes of a fleet of AFVs, based on a single depot, serving a set of customers, geographically distributed, while minimizing the total travel distance. Each AFV starts/ends from/to the depot, respecting both the limited cargo and fuel tank capacity. For refueling reasons, intermediate stops to the AFSs have been also planned to prevent drivers remaining without the minimum fuel level to either reach an AFS or return to depot. The G-VRP has been addressed from both the modeling and methodological point of view and generally, to allow multiple visits at the AFSs, dummy copies of them are introduced consequently increasing the problem complexity. In this work, a new Mixed Integer Linear Programming formulation for the GVRP is proposed in which the visits to the AFSs are only implicitly considered, avoiding dummy copies. Moreover, the number of variables is reduced also by pre-computing, for each pair of customers, an efficient set of AFSs, given by only those that may be actually used in an optimal solution. Numerical experiments, carried out on benchmark instances, extending those presented in [3], show that our model, solved through an optimization tool software, outperforms the previous ones proposed in the literature [1,2]. Moreover, it allows certifying optimal solutions also for instances previously not solved to optimality.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245668

A Three-Phase Matheuristic for the Time-Effective Electric Vehicle Routing Problem with Partial Recharges
Book of abstracts of the 4th International Conference on Variable Neighborhood Search
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella; Suraci, Stefano
Luogo di pubblicazione: Malaga
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: We propose a three-phase matheuristic, combining an exact method with a Variable Neighborhood Search local Branching (VNSB) to route a fleet of Electric Vehicles (EVs). EVs are allowed stopping at the recharging stations along their routes to (also partially) recharge their batteries. We hierarchically minimize the number of EVs used and the total time spent by the EVs, i.e., travel times, charging times and waiting times (due to the customer time windows). The first two phases are based on Mixed Integer Linear Programs to generate feasible solutions, used in a VNSB algorithm. Numerical results on benchmark instances show that the proposed approach finds good quality solutions in reasonable amount of time .
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245757

A multi-objective optimization for relocating electric vehicles in car-sharing services
Book of Abstracts of the Fifth meeting of the EURO working group on Vehicle Routing and Logistics optimization (VeRoLog 2016)
Autore/i: Pisacane, Ornella; Bruglieri, Maurizio; Pezzella, Ferdinando
Luogo di pubblicazione: Nantes
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Nowadays, also thanks to the Information and Communication Technology, the sharing mobility represents a significant part of the sharing economy. In particular, the Car Sharing Services (CSSs), in which the user rents a car for short time, paying according to the time of use, support the sustainable mobility, reducing the number of parked vehicles and consequently, the traffic congestion, noise and air pollution. These two last advantages are more guaranteed in CSSs with Electric Vehicles (EVs). In fact, the EVs guarantee zero local CO2 emissions and are less noisy than the traditional combustion engine vehicles. In particular, in One-way CSSs (OCSS), a user can drop off a vehicle in a parking station different from the pickup one. However, the OCSSs suffer of possible imbalances between the demand and the supply of vehicles, leading to a Vehicle RElocation Problem (VREP). We address a VREP in OCSSs with EVs in which the relocation is operator-based: the CSS operators relocate the EVs by directly driving them from a station of pickup to one of delivery and move from a station of delivery to one of pickup by folding bikes. To balance the good quality of service assured to the users (maximizing the number of EV requests satisfied), the cost reduction and the load balancing among the operators, a multiobjective VREP is solved. Firstly, a set of feasible solutions is heuristically generated and then, through the epsilon-constraint method, a three-objective non-overlapping model is solved. Numerical results are carried out on some benchmark instances.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245666

On the economic sustainability of supplying bandwidth policies in multi-layer wireless cognitive networks
APPLIED MATHEMATICAL MODELLING
Autore/i: Aloi, G.; Grandinetti, L.; Pace, P.; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: Nowadays, advanced inventory management policies guarantee cost reductions and higher service levels, making them very attractive for modern and challenging communication scenarios such as those related to Multi-layer Wireless Cognitive Networks (MWCNs). In these systems, the radio resources can be considered extremely perishable “commodities” with a short-term lifetime. After describing the latest state of the art on this topic, the novelty of the paper is in being the first to adapt the NewsVendor model from Logistics in order to guarantee a cost-effective bandwidth provisioning in MWCNs. Then, we study the economic sustainability of the proposed approach compared to the one based on the adaptive period inventory management policy, already presented in the literature. Numerical results show that the NewsVendor model outperforms the adaptive period inventory management policy in all the cases under investigation. It provides decision makers with more stable supply solutions by taking into consideration both the randomness of the bandwidth requirements and its short-term lifetime. In addition, it also improves both the total profit and user satisfaction levels.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253226

A new Mathematical Programming Model for the Green Vehicle Routing Problem
Proceedings of 14th Cologne Twente Workshop (CTW 2016)
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella
Editore: Università degli Studi di Milano
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: A new MILP formulation for the Green Vehicle Routing Problem is introduced where the visits to the Alternative Fuel Stations (AFSs) are only implicitly considered. The number of variables is also reduced by pre-computing for each couple of customers an efficient set of AFSs, only given by those that may be actually used in an optimal solution. Numerical experiments on benchmark instances show that our model outperforms the previous ones proposed in the literature.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245667

A new Mathematical Programming Model for the Green Vehicle Routing Problem
ELECTRONIC NOTES IN DISCRETE MATHEMATICS
Autore/i: Bruglieri, Maurizio; Mancini, Simona; Pezzella, Ferdinando; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: A new MILP formulation for the Green Vehicle Routing Problem is introduced where the visits to the Alternative Fuel Stations (AFSs) are only implicitly considered. The number of variables is also reduced by pre-computing for each couple of customers an efficient set of AFSs, only given by those that may be actually used in an optimal solution. Numerical experiments on benchmark instances show that our model outperforms the previous ones proposed in the literature
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245663

A pick-up and delivery problem with time windows by electric vehicles
INTERNATIONAL JOURNAL OF PRODUCTIVITY AND QUALITY MANAGEMENT
Autore/i: Grandinetti, Lucio; Guerriero, Francesca; Pezzella, Ferdinando; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: In the pick-up and delivery problem with time windows (PDPTW), each transportation service is delivered, from an origin to a destination, satisfying both the time windows and the precedence constraints. This paper addresses the related vehicle routing problem by using only electric vehicles (EVs) and by introducing the recharging stations (RSs). The problem is formulated as a multi-objective mixed integer linear model for minimising the total travel distance, the total cost for the EVs used and the total penalty cost for the unsatisfied time windows. In addition, length constraints on the routes are imposed in order to include several aspects such as the limited availability of the RSs. The weighted sum method is adopted and, to properly set the weights, three methods, derived from the analytical hierarchical process, are compared. Computational experiments on some instances are carried out, in order to assess the behaviour of our approach in terms of solution quality
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245662

Solving the Electric Vehicle Routing Problem with Time Windows and Partial Recharges
Fourth meeting of the EURO Working Group on Vehicle Routing and Logistics Optimization (VeRoLog 2015)
Autore/i: Pisacane, Ornella; Bruglieri, Maurizio; Pezzella, Ferdinando; Suraci, Stefano
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Electromobility aims promoting transportation solutions employing the Electric Vehicles (EVs) in place of the traditional internal combustion engine vehicles in order to reduce the harmful CO2 emissions that are polluting more and more the big cities. In addition, the recent technological progresses concerning the EVs allow also partial battery recharges. In this context, the aim of our work is to efficiently route a fleet of EVs, exploiting such recent technological advancements, in order to handle a set of customers within their time windows. Each EV route starts/ends from/at a common depot. Moreover, along each route, intermediate stops at the recharging stations for (also partial) battery recharges are allowed. The problem, known as Electric Vehicle Routing Problem with Time Windows, is here mathematically formulated as a Mixed Integer Linear Program (MILP) with the aim of firstly minimizing the number of EVs used and then, of optimizing the total time spent by the EVs outside the depot i.e., the total recharging, traveling and waiting times. In order to handle the problem hardness and to find good quality solutions in real life settings, a matheuristic, based on the Variable Neighborhood Search, is proposed. Numerical results, carried out on some benchmark instances, are shown for the solutions found by both the proposed MILP and the matheuristic.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/245665

A Variable Neighborhood Search Branching for the Electric Vehicle Routing Problem with Time Windows
ELECTRONIC NOTES IN DISCRETE MATHEMATICS
Autore/i: Bruglieri, Maurizio; Pezzella, Ferdinando; Pisacane, Ornella; Suraci, Stefano
Classificazione: 1 Contributo su Rivista
Abstract: E-mobility plays a key role especially in contexts where the transportation activities impact a lot on the total costs. The Electric Vehicles (EVs) are becoming an effective alternative to the internal combustion engines guaranteeing cheaper and eco-sustainable transport solutions. However, the poor battery autonomy is still an Achille's hell since the EVs require many stops for being recharged. We aim to optimally route the EVs for handling a set of customers in time considering the recharging needs during the trips. A Mixed Integer Linear Programming formulation of the problem is proposed assuming that the battery recharging level reached at each station is a decision variable in order to guarantee more flexible routes. The model aims to minimize the total travel, waiting and recharging time plus the number of the employed EVs. Finally, a Variable Neighborhood Search Branching (VNSB) is also designed for solving the problem at hand in reasonable computational times. Numerical results on benchmark instances show the performances of both the mathematical formulation and the VNSB compared to the ones of the model in which the battery level reached at each station is always equal to the maximum capacity
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/225069

Comparing heuristics for the product allocation problem in multi-level warehouses under compatibility constraints
APPLIED MATHEMATICAL MODELLING
Autore/i: Guerriero, F.; Pisacane, O.; Rende, F.
Classificazione: 1 Contributo su Rivista
Abstract: One of the most significant activities in warehouse management concerns the allocation of products to the storage positions. This problem is known in the literature as the Product Allocation Problem (PAP). It mainly aims to optimize both the warehouse space utilization and the products handling costs (at least 40% of the total logistics cost). This paper addresses the PAP in a multi-layer warehouse, with compatibility constraints among the product classes. It has already been addressed from a modeling point of view in the literature and it has been formulated as a Mixed Integer Linear Programming model. However, solving the problem to optimality becomes impracticable in real-life settings. To this purpose, an Iterated Local Search-based Heuristic ( ILS ) and a Cluster-based Heuristic ( CH ) have already been proposed in the literature. This paper presents a Rollout-based heuristic whose performances are evaluated on the basis of a detailed computational phase, including also a real case study and compared with those of both the ILS and the CH , in terms of the computational times and the quality of the final solutions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253216

A Time effective Optimization model for the Electric Vehicle Routing Problem with Time Windows
DECISION MODELS for SMARTER CITIES
Autore/i: Pisacane, O.; Bruglieri, M.; Suraci, S.
Editore: Politecnico di Milano
Luogo di pubblicazione: Milano
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Nowadays, the use of Electric Vehicles (EVs) is increasing in both the public and the private urban transportation systems. They are also employed in the last mile transportation services and to access to the Limited Traffic Zones. The main advantages are in a reduction of both the use of fossil fuels and the harmful CO2 emissions. However, even though significant improvements of their performances have been reached in the last years, the limited battery autonomy in terms of travelled kilometers still remains a critical issue. Consequently, stops at recharging stations are usually required during the trips. This work addresses the problem of optimally routing an EV fleet in order to handle the customer demands. Each customer request is specified in terms of a time window and a demand. The related optimization problem (also known as the Electric Vehicle Routing Problem with Time Windows, E-VRPTW) has been already addressed in the literature [1,3]. Due to the particular features of the EVs, the E-VRPTW has been mathematically formulated including the need of using the Recharging Stations (RSs) during the trips [2]. However, the EVs are always fully recharged at the RSs and the goal is to minimize both the number of used EVs and the total travelled distance. We propose a variant of the original E-VRPTW such that the batteries are not necessarily fully charged. Consequently, the partial recharges guarantee higher flexibility during the route planning. Then, for each EV, the level of battery, recharged at a RS, is a decision variable of the optimization process. Moreover, the objective function takes into account also the total waiting time of each EV at each served customer and the total recharging time. The resulting proposed mathematical model is a Mixed Integer Linear Program formulation of the E-VRPTW. Finally, computational results on instances taken from the literature are compared to the ones described in [2].
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253250

Multi-objective optimization in dial-and-ride public transportation
Book of abstract of 17th meeting of the EURO WORKING GROUP ON TRANSPORTATION
Autore/i: Guerriero, F.; Pezzella, F.; Pisacane, O.; Trollini, L.
Editore: University of Seville
Luogo di pubblicazione: Siviglia
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: In the Dial-And-Ride public transportation systems, each customer requirement is specified in terms of a pickup (origin), of a delivery (destination) and of a time window within it has to be satisfied. The aim is to find a set of routes, each assigned to a vehicle, in order to satisfy the set of requests, under capacity, time windows, precedence and pairing conditions. In fact, it is usually assumed that the service demand of a request, picked up at its origin, is exactly delivered at its destination (one-to-one service) and that the fleet of the vehicles is based at a single-depot. From a modeling point of view, the problem could be addressed as a one-to-one capacitated Pickup and Delivery Problem with Time Windows (PDPTW) and therefore, the mathematical formulation presents, beyond the traditional capacity constraints on the vehicles, also the pairing, the precedence and the time windows conditions. In particular, the pairing conditions guarantee that each couple (pickup, delivery) has to belong to the same route while the precedence constraints impose that each pickup has to be served before the associated delivery. The contribution of this paper mainly consists in addressing the problem with the aim of finding a set of feasible routes by optimizing, at the same time, two objectives such as the maximum ride time and the total waiting time. Therefore, a bi-objective time constrained PDPTW is proposed and solved by implementing a two-step approach. In particular, the first step heuristically determines a set of feasible routes, used by the second step based on a set partitioning mathematical formulation and the constraint method to generate efficient solutions. The control parameters of the heuristics, used in the first step, are properly set by adopting a F-Race based approach. Computational experiments on some benchmark instances are carried out to assess the behavior of the proposed approach in finding good quality Pareto Efficient solutions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/182102

A Variable Neighborhood Search Branching for the Electric Vehicle Routing Problem with Time Windows
Abstract Booklet- 3rd International Conference on Variable Neighborhood Search
Autore/i: Bruglieri, M.; Pezzella, Ferdinando; Pisacane, O.; Suraci, Stefano
Editore: MODILS, FSEG, Sfax University
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: E-mobility plays a key role especially in contexts where the transportation activities impact a lot on the total costs. The Electric Vehicles (EVs) are becoming an effective alternative to the internal combustion engines guaranteeing cheaper and eco-sustainable transport solutions. However, the poor battery autonomy is still an Achille’s hell since the EVs require many stops for being recharged. We aim to optimally route the EVs for handling a set of customers in time considering the recharging needs during the trips. A Mixed Integer Linear Programming formulation of the problem is proposed assuming that the battery recharging level reached at each station is a decision variable in order to guarantee more flexible routes. The model aims to minimize the total travel, waiting and recharging time plus the number of the employed EVs. Finally, a Variable Neighborhood Search Branching (VNSB) is also designed for solving the problem at hand in reasonable computational times. Numerical results on benchmark instances show the performances of both the mathematical formulation and the VNSB compared to the ones of the model in which the battery level reached at each station is always equal to the maximum capacity.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/221713

The multi-objective multi-vehicle pickup and delivery problem with time windows
PROCEDIA: SOCIAL & BEHAVIORAL SCIENCES
Autore/i: Grandinetti, L.; Guerriero, F.; Pezzella, F.; Pisacane, O.
Classificazione: 1 Contributo su Rivista
Abstract: The Single Objective Single Vehicle Pickup and Delivery Problem (SOSV-PDP) is a Vehicle Routing Problem (VRP)in which the vehicle, based at the depot, has to visit exactly once a set of customers with known demand. Each request specifies two locations: an origin for the picking and one for the delivery. The vehicle must start and finish at the depot and the total handled demand must not exceed its capacity. Moreover, for each request, the origin must precede the destination (precedence constraints). In the SOSV-PDP with Time Windows (SOSV-PDPTW), each request specifies also a time window. Therefore, the vehicle has to serve the customer within the time window (time window constraint). The Single Objective Multiple Vehicle-PDPTW (SOMV-PDPTW) is an extension of SOSV-PDPTW where customers are served by a fleet (usually homogeneous) of vehicles. Therefore, together with the precedencies, for each request, the origin and the destination have to belong to the same route (pairing constraints). In the traditional SOMV-PDPTW, only one objective is optimized (usually, the total travel cost); while, in the literature, few multi-objective MOMV-PDPTW exist that optimize at most three criteria simultaneously. The contribution of this paper consists in addressing the MOMV-PDPTW from both a modeling and methodological point of view. In fact, the MOMV-PDPTW is firstly modeled with the aim of optimizing the number of vehicles, the total travel cost and the longest travel cost, simultaneously; then, a two-step solution approach is proposed. In particular, in the first step, a set of feasible routes is generated by properly adapting some meta-heuristics proposed in literature for the SOMV-PDPTW, then, set partitioning optimization problems are solved within an c-constraint framework. More specifically, each set partitioning problem selects the routes from the feasible set, optimizing one criterion at time, constraining the remaining ones by appropriate upper bounds and satisfying customer requirements. Finally, the second step finds the set of efficient solutions for approximating the Pareto Fronts. Computational experiments, carried out on some instances generated in literature, show that our approach determines good quality Efficient Pareto Fronts (in terms of number of efficient solutions) and also provides well-diversified efficient sets. This last aspect is properly evaluated by computing the Spread metric on each of the instances.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/155307

Multi-objective Optimization in Dial-a-ride Public Transportation
TRANSPORTATION RESEARCH PROCEDIA
Autore/i: Guerriero, F.; Pezzella, F.; Pisacane, O.; Trollini, L.
Classificazione: 1 Contributo su Rivista
Abstract: In the Dial-a-Ride public transportation systems, each customer requirement is specified in terms of a pickup (origin), of a delivery (destination) and of a time window within it has to be satisfied. The aim is to find a set of routes, each assigned to a vehicle, in order to satisfy the set of requests, under capacity, time windows, precedence and pairing conditions. It is usually assumed that the demand of a request, picked up at its origin, is exactly delivered at its destination (one-to-one service) and that the fleet of the vehicles is based at a single depot. From a modelling point of view, the problem could be addressed as a one-to-one capacitated Pickup and Delivery Problem with Time Windows (PDPTW) and therefore, the mathematical formulation presents, beyond the traditional capacity constraints on the vehicles, also the pairing, the precedence and the time windows conditions. In particular, the pairing conditions guarantee that each couple (pickup, delivery) has to belong to the same route while the precedence constraints impose that each pickup has to be served before the associated delivery. This paper addresses the problem with the aim of optimizing, at the same time, the maximum total ride time and the total waiting time. Then, a bi-objective PDPTW with a constraint on the maximum duration of each route is proposed and solved by a two-step approach. In particular, the first step determines a set of feasible routes by meta-heuristics. These routes are used in second step in a bi-objective set partitioning formulation solved by the epsilon-constraint method to generate efficient solutions. The parameters of the meta-heuristics are properly set by a racing procedure. Computational experiments on some benchmark instances are carried out to assess the performance of the proposed approach
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/201711

Damped Techniques for the Limited Memory BFGS Method for Large-Scale Optimization
JOURNAL OF OPTIMIZATION THEORY AND APPLICATIONS
Autore/i: Al-Baali, Mehiddin; Grandinetti, Lucio; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: This paper is aimed to extend a certain damped technique, suitable for the Broyden–Fletcher–Goldfarb–Shanno (BFGS) method, to the limited memory BFGS method in the case of the large-scale unconstrained optimization. It is shown that the proposed technique maintains the global convergence property on uniformly convex functions for the limited memory BFGS method. Some numerical results are described to illustrate the important role of the damped technique. Since this technique enforces safely the positive definiteness property of the BFGS update for any value of the steplength, we also consider only the first Wolfe–Powell condition on the steplength. Then, as for the backtracking framework, only one gradient evaluation is performed on each iteration. It is reported that the proposed damped methods work much better than the limited memory BFGS method in several cases.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253225

The multi-objective multi-vehicle pickup and dlivery problem with time windows
Book of abstracts of EURO Working Group on Transportation Conference (EWGT 2013)
Autore/i: Grandinetti, L.; Guerriero, F.; Pezzella, Ferdinando; Pisacane, O.
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/155324

Effective supplying bandwidth policies for wireless cognitive networks: A logistics approach
IEEE International Symposium on Personal, Indoor and Mobile Radio Communications, PIMRC
Autore/i: Pace, Pasquale; Aloi, Gianluca; Pisacane, Ornella
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Nowadays, new communication paradigms such as those related to wireless cognitive networks, can take great advantages from advanced inventory management policies by considering radio resources as an extremely perishable commodity with a short-term life time. Starting from this challenging and multidisciplinary research field, the paper proposes to adapt the NewsVendor model, coming from Logistics, to guarantee an effective bandwidth provisioning for cognitive networks also drawing a comparison with a classical adaptive period inventory management policy. Numerical results, validated throughout simulation campaigns, confirm that the NewsVendor model always outperforms the adaptive period inventory management policy by improving both the total profit and the user satisfaction levels.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253231

A mathematical model for the Multi-Levels Product Allocation Problem in a warehouse with compatibility constraints
APPLIED MATHEMATICAL MODELLING
Autore/i: Guerriero, F.; Musmanno, R.; Pisacane, O.; Rende, F.
Classificazione: 1 Contributo su Rivista
Abstract: The aim of this work is to address the products allocation problem in a multi-layers warehouse with compatibility constraints among the classes. The problem under study represents one of the most relevant topic in Logistics. The goal is to reduce, as much as possible, the delivery times; the inventories; the total logistic costs and to guarantee, at the same time, higher service levels (i.e., high customers satisfaction degree). In this work, a linear model to mathematically represent the problem is developed and its performance is evaluated on a set of instances, representing realistic situations. A sensitivity analysis is also carried out by considering the most relevant parameters of the model. Finally, an Iterated Local Search based heuristic is defined in order to solve large scale scenarios in a reasonable amount of time. Numerical results show that the proposed heuristic is able to find good quality solutions with a computational effort lower than that required to solve the proposed mathematical model.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253222

An approximate epsilon-constraint method for a multi-objective job scheduling in the cloud
FUTURE GENERATION COMPUTER SYSTEMS
Autore/i: Grandinetti, L.; Pisacane, O.; Sheikhalishahi, M.
Classificazione: 1 Contributo su Rivista
Abstract: Cloud computing is a hybrid model that provides both hardware and software resources through computer networks. Data services (hardware) together with their functionalities (software) are hosted on web servers rather than on single computers connected by networks. Through a device (e.g., either a computer or a smartphone), a browser and an Internet connection, each user accesses a cloud platform and asks for specific services. For example, a user can ask for executing some applications (jobs) on the machines (hosts) of a cloud infrastructure. Therefore, it becomes significant to provide optimized job scheduling approaches suitable to balance the workload distribution among hosts of the platform. In this paper, a multi-objective mathematical formulation of the job scheduling problem in a homogeneous cloud computing platform is proposed in order to optimize the total average waiting time of the jobs, the average waiting time of the jobs in the longest working schedule (such as the makespan) and the required number of hosts. The proposed approach is based on an approximate ϵ-constraint method, tested on a set of instances and compared with the weighted sum (WS) method. The computational results highlight that our approach outperforms the WS method in terms of a number of non-dominated solutions.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253227

Pervasive cloud computing technologies: Future outlooks and interdisciplinary perspectives
Autore/i: Grandinetti, Lucio; Pisacane, Ornella; Sheikhalishahi, Mehdi
Editore: IGI Global
Luogo di pubblicazione: HERSHEY, PENNSYLVANIA
Classificazione: 3 Libro
Abstract: Technology trends may come and go, but cloud computing technologies have been gaining consideration in the commercial world due to its ability to provide on-demand access to resources, control the software environment, and supplement existing systems. Pervasive Cloud Computing Technologies: Future Outlooks and Interdisciplinary Perspectives explores the latest innovations with cloud computing and the impact of these new models and technologies. This book will present case studies and research on the future of cloud computing technologies and its ability to increase connectivity of various entities of the world. It is an essential resource for technology practitioners, engineers, managers, and academics aiming to gain the knowledge of these novel and pervasive technologies.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253215

A pickup and delivery problem with time Windows by electric vehicles
Proceedings of XVIII Summer School "Francesco Turco"
Autore/i: Grandinetti, L.; Guerriero, F.; Pezzella, F.; Pisacane, O.
Editore: AIDI - Italian Association of Industrial Operations Professors
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The Pickup and Delivery Problem with Time Windows (PDPTW) is a Vehicle Routing Problem with Time Windows (VRPTW) in which each customer, together with a demand and a time window for the service, specifies also an origin (pickup) and a destination (delivery). Our work manly extends the PDPTW to the case in which the fleet consists of electric vehicles (E-PDPTW), in order to exploit their significant advantages in terms of energy saving and sustainability. The E-PDPTW is then modeled as a multi-objective optimization problem in order to minimize the total travel distance, the total cost due to the used electric vehicles and the penalties due to the delayed services. In addition, beyond the classical vehicle routing constraints, in order to consider the practical difficulties due to the limited battery life of the electric vehicles (EVs) and to the poor availability of the recharging stations, some additional constraints are also imposed. The problem is then formulated as a multiobjective mathematical programming model and solved by applying the Weighted Sum Method (WSM) with weights determined by an approach derived from the Analytical Hierarchical Process (AHP).
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/155318

A CLUSTER-BASED HEURISTIC FOR ALLOCATING PRODUCTS IN MULTILEVELS WAREHOUSES
Proceedings of The 2012 International Conference on Logistics and Maritime Systems
Autore/i: Guerriero, Francesca; Mari, Francesco; Musmanno, Roberto; Pisacane, Ornella; Rende, Francesco
Editore: University of Bremen
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: One of the major issues in Warehouse Management is to optimally assign the product classes to the storage locations (slots, for short) on the basic principle that the most required items have to be allocated closer to the I/O doors (Products Allocation Problem-PAP). The aim of this paper is to study a special version of PAP considering a multi-layers warehouse with compatibility constraints among the classes (two aspects that, at the best of our knowledge, have not been addressed in scientific literature yet). First, we modelled the problem (as already described in Guerriero et al (2012)) with the aim of minimizing the total logistics costs (due to the handling operations and the products decentralization in the warehouse) satisfying specific operational constraints (for example, compatibility and capacity constraints). However, since on large-scale instances the complexity of the model (in terms of number of decision variables and constraints) becomes computationally intractable by optimization solvers, we also design, implement and test a cluster-based heuristic approach for overcoming this limitation. Finally, we compare the results from two points of views: the solutions quality and the computational overhead.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253246

An optimization-based heuristic for the multi-objective undirected capacitated arc routing problem
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Grandinetti, L.; Guerriero, F.; Laganá, D.; Pisacane, O.
Classificazione: 1 Contributo su Rivista
Abstract: The Multi-objective Undirected Capacitated Arc Routing Problem (MUCARP) is the optimization problem aimed at finding the best strategy for servicing a subset of clients localized along the links of a logistic network, by using a fleet of vehicles and optimizing more than one objective. In general, the first goal consists in minimizing the total transportation cost, and in this case the problem brings back to the well-known Undirected Capacitated Arc Routing Problem (UCARP). The motivation behind the study of the MUCARP lies in the study of real situations where companies working in the logistic distribution field deal with complex operational strategies, in which different actors (trucks, drivers, customers) have to be allocated within an unified framework by taking into account opposite needs and different employment contracts. All the previous considerations lead to the MUCARP as a benchmark optimization problem for modeling practical situations. In this paper, the MUCARP is heuristically tackled. In particular, three competitive objectives are minimized at the same time: the total transportation cost, the longest route cost (makespan) and the number of vehicles (i.e., the total number of routes). An approximation of the optimal Pareto front is determined through an optimization-based heuristic procedure, whose performances are tested and analyzed on classical benchmark instances.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253221

Web services for healthcare management
Technologies and Protocols for the Future of Internet Design: Reinventing the Web
Autore/i: Grandinetti, Lucio; Pisacane, Ornella
Editore: IGI Global
Classificazione: 2 Contributo in Volume
Abstract: Nowadays, Health Care Organizations (HCOs) are interested in defining methodologies of Information Technology (IT) for providing high quality services at minimum cost. Through modern software and hardware, they can process data and manage the three important phases: diagnosis, prognosis, and therapy. In this scenario, Web Technologies (WTs) can: provide advanced Information Systems that combine software applications; offer a heterogeneous connectivity to users; allow costs reduction; improve the delivery of the services; guarantee an interactive support of the doctors, interconnectivity between the HCOs, and effective information sharing. In this chapter, first it is described how to provide the services of a HCO through the WTs, and then it is shown how Operations Research makes it more effective, to deal with, for example, clinical data classification problem, clinical predictions, clinical what-if analysis, and Web services composition process.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253232

A wise cost-effective supplying bandwidth policy for multilayer wireless cognitive networks
COMPUTERS & OPERATIONS RESEARCH
Autore/i: Aloi, G.; Musmanno, R.; Pace, P.; Pisacane, O.
Classificazione: 1 Contributo su Rivista
Abstract: Inventory management is one of the most important research areas in Operations Research and Logistics. It mainly aims to efficiently manage inventories at different facilities (for example, warehouses and plants in Supply Chains (SCs)), minimizing the total cost and satisfying the service levels. Some exact inventories management approaches are successfully proposed and applied to different real scenarios, traditionally related to the SCs, even if the extreme versatility of these techniques could make them attractive to new challenging scenarios such as those related to telecommunications networks. Starting from this vision, the focus of this paper is to show the new benefits of applying an adaptive period inventory management policy to a wireless cognitive telecommunication scenario in which radio transmission resources are treated as short-term life time goods which supplies wisely in order to maximize both economic profit and quality of service offered to wireless users. The system behavior is tested using an agent-based simulator and computational results show that introducing this wise control on the bandwidth supplying mechanism guarantees a more reactive and effective telecommunication network, reaching a good compromise between the total profit and the service levels.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253220

The Product Allocation Problem in a Warehouse with Compatibility and Volume Balancing Constraints
Abstract book of the 42nd Annual Conference of the Italian Operational Research Society, Operational Research in Transportation and Logistics
Autore/i: Pisacane, O; Guerriero, F; Rende, F; Simini, M
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: The organizations are interesting in adopting supply chain management policies for reducing the total costs. In this context, the improvement of each specific activity plays a crucial role: for example, managing efficiently the storage space in a warehouse. It arises to a specific problem, known as Product Allocation Problem (PAP). PAP influences many performance measures of a warehouse (order-picking time and cost, productivity, inventory accuracy and etc.) and thus this problem has attracted the attention of many researchers, interested in developing efficient models and approaches. The traditional solution strategy firstly groups the products in classes (considering their structure and characteristics) and, then, assigns each class to a slot of the storage space. In this work, we firstly present a mathematical model including both compatibility constraints (i.e., two classes could not be located in adjacent slots) and volume constraints for placing each class into the assigned slot. Since in realistic scenarios (many product classes and slots in the warehouse) the mathematical formulation could become computationally intractable, we also describe a two steps heuristic for solving the considered problem in a reasonable amount of time.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253248

Web based prediction for diabetes treatment
FUTURE GENERATION COMPUTER SYSTEMS
Autore/i: Grandinetti, Lucio; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: Diabetics need continuous support during their therapy because the clinical treatment could be improved in the medical cures;the doctors need to share the new information and to support their patients in an interactive way. In this paper, we describe a web based software tool able to perform predictions on the future glycaemia level of the patients for a specific time horizon; to perform what-if analysis, showing how the glycaemia level could vary if some parameters are changed (either in the diet of the patient or in the clinical treatment); to share information and suggestions, creating a virtual community between specialists and patients; to inform users about their health condition, by a classification algorithm and to allow the patient to maintain a daily diary and to know about the evolution of the health condition. The system merges software engineering and Operation Research methods and could become a valid interactive support for patients and specialists.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253219

Optimizing daily agent scheduling in a multiskill call center
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH
Autore/i: Avramidis, Athanassios N.; Chan, Wyean; Gendreau, Michel; L'Ecuyer, Pierre; Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: We examine and compare simulation-based algorithms for solving the agent scheduling problem in a multiskill call center. This problem consists in minimizing the total costs of agents under constraints on the expected service level per call type, per period, and aggregated. We propose a solution approach that combines simulation with integer or linear programming, with cut generation. In our numerical experiments with realistic problem instances, this approach performs better than all other methods proposed previously for this problem. We also show that the two-step approach, which is the standard method for solving this problem, sometimes yield solutions that are highly suboptimal and inferior to those obtained by our proposed method.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253218

An approximate epsilon-constraint method for the multi-objective undirected capacitated arc routing problem
International Symposium on Experimental Algorithms
Autore/i: Grandinetti, Lucio; Guerriero, Francesca; Lagana', Demetrio; Pisacane, Ornella
Editore: Springer
Luogo di pubblicazione: Berlin, Heidelberg
Classificazione: 2 Contributo in Volume
Abstract: The Undirected Capacitated Arc Routing Problem is a classical arc routing problem arising in practical situations (road maintenance, garbage collection, mail delivery, school bus routing, etc.) with the aim of minimizing the total transportation cost of a set of routes that service a set of required edges under capacity constraints. Most of logistic companies are interested in minimizing not only the total transportation cost, they also are focused in managing the deliveries on the edges, in such a way that the duration of the longest trip does not exceed an upper time limit, to take into account the working day duration of the drivers. Moreover, all the demands of the required edges are satisfied by considering a limited number of vehicles at the depot. In this paper, the Multi-objective Undirected Capacitated Arc Routing Problem where different and competitive objectives are taken into account simultaneously, is defined and studied. Three objectives are considered in order to: minimize the total transportation cost, the longest route (makespan) and the number of vehicle used to service all the required edges (i.e., the total number of routes). To find a set of solutions belonging to the optimal pareto front, an optimization-based heuristic procedure is proposed and its performance is evaluated on a set of benchmark instances.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253211

Heuristic Approaches for the Multiobjective Capacitated Arc Routing Problem
Decision and optimization models for evaluation and management
Autore/i: Grandinetti, L; Lagana'D, ; Guerriero, F; Pisacane, O
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253249

Metodi Simulativi
Modelli e metodi decisionali in condizioni di incertezza e rischio
Autore/i: Legato, P; Pisacane, O
Editore: McGraw – Hill Italia
Luogo di pubblicazione: MILANO
Classificazione: 2 Contributo in Volume
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253247

A general distributed framework based on iterated local search
Proceedings of the 5th IEEE International Workshop on Intelligent Data Acquisition and Advanced Computing Systems: Technology and Applications, IDAACS'2009
Autore/i: Pisacane, Ornella; Attanasio, Andrea; Guerriero, Francesca; Musmanno, Roberto
Editore: IEEE
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: Some optimization problems are too complex to be solved exactly, using specific software tools. For this reason, in many cases it is more convenient to define and design a heuristic procedure even though the final solution is generally sub-optimal. One of the most promising approaches in the traditional computing environment is the Iterated Local Search method. It is based on an exploration of the neighbor of the current solution and its performance is estimated to be very high for a large number of problems. The main drawback of the approach could be the required computational time, in particular when the neighbor to be explored becomes too large. We propose a general distributed framework, based on Iterated Local Search, and we show a concrete application in logistics, related to the optimal assignment of products to storage locations in a warehouse.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253223

Agent scheduling in a multiskill call center
4OR
Autore/i: Pisacane, Ornella
Classificazione: 1 Contributo su Rivista
Abstract: This is a summary of the author’s PhD thesis, supervised by Pierre L’Ecuyer and Roberto Musmanno and defended on 21 February 2008 at the Università della Calabria. The thesis is written in English and is available from the author upon request. This work deals with the comparison of simulation-based algorithms for solving the agents scheduling problem in a multiskill call center minimizing their costs under service levels constraints. A solution approach, combining simulation, with integer or linear programming, and cut generation, is proposed. Considering realistic problems, it performs better than the two-step approach proposed in the literature. It is also shown that a randomized search, extending the one defined for the single-period staffing problem in Avramidis et al. [IIE Trans (in press), 2008], yields highly suboptimal solutions. Finally, an extension of the cutting plane method to directly control the probability on the customers abandonments is designed
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253230

A Web3D application for the Bin-Packing Problem
20th European Modeling and Simulation Symposium, EMSS 2008
Autore/i: Bruno, Fabio; Caruso, Francesco; Pisacane, Ornella; Musmanno, Roberto; Muzzupappa, Maurizio; Rende, Francesco; Giovanni, Venuto
Editore: DIPTIM-UNIV GENOA
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: This paper describes a web application for supporting the user in the assessment of the optimal loading configuration for several carriers (i.e. trucks, containers, ship, etc.). The application has a standard form-based user-interface to insert data of the available carriers and items have to be loaded. The solution of this problem (known as Bin-Packing Problem (BPP)) is found by a specific algorithm and visualized by a 3D graphics representation inside the web page. Although some commercial applications already exist, ours runs directly on the web and offers, at the same time, an efficient and robust solver and a 3D visualization allowing the user to better understand the localization of the items inside the carrier and to interactively change some of the problem constraints directly on the 3D representation.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253233

Web services for optimal clinical support systems
Proceedings of the 2008 International Conference on Semantic Web and Web Services, SWWS 2008
Autore/i: Grandinetti, Lucio; Pisacane, Ornella
Editore: CSREA Press
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253235

ANTURPP: An ant colony heuristic for the undirected rural postman problem
Optimization and Decision Sciences
Autore/i: Laganà, Demetrio; Mari, Francesco; Musmanno, Roberto; Pisacane, Ornella
Editore: PRIMA Soc. Coop. a r. l.
Luogo di pubblicazione: Genova
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253251

An Ant Colony Optimization Metaheuristic for the Undirected Rural Postman Problem
Technical Report Les Cahiers du GERAD, G–2007–106
Autore/i: Lagana', Demetrio; Laporte, Gilbert; Mari, Francesco; Musmanno, Roberto; Pisacane, Ornella
Luogo di pubblicazione: Montrèal
Classificazione: 5 Altro
Abstract: This paper describes a new heuristic for the well-known Undirected Rural Postman Problem. It consists of two steps: it first constructs a partial solution using the Ant Colony Optimization metaheuristic, and the remaining required edges are then gradually inserted. Computational results on a set of benchmark instances are presented and comparisons with alternative heuristics are performed. The optimality gap is also computed by running a branch-and-cut algorithm
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253236

Simulation-based optimization of agent scheduling in multiskill call centers
5th International Industrial Simulation Conference 2007, ISC 2007
Autore/i: Avramidis, Athanassios N.; Gendreau, Michel; L'Ecuyer, Pierre; Pisacane, Ornella
Editore: EUROSIS
Classificazione: 4 Contributo in Atti di Convegno (Proceeding)
Abstract: We examine and compare simulation-based algorithms for solving the agent scheduling problem in a multiskill call center. This problem consists in minimizing the total costs of agents under constraints on the expected service level per call type, per period, and aggregated. We propose a solution approach that combines simulation with integer or linear programming, with cut generation. In our numerical experiments with realistic problem instances, this approach performs better than all other methods proposed previously for this problem. We also show that the two-step approach, which is the standard method for solving this problem, sometimes yield solutions that are highly suboptimal and inferior to those obtained by our proposed method.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253234

Solving simulation optimization problems on grid computing systems
PARALLEL COMPUTING
Autore/i: Laganá, Demetrio; Legato, Pasquale; Pisacane, Ornella; Vocaturo, Francesca
Classificazione: 1 Contributo su Rivista
Abstract: The optimal assignment of berth slots and cranes to shipping services is the central logistics problem at modern marine container terminals and should be formulated to specifically account for its stochastic nature. We use a computational grid to solve a major seaport logistic problem by a simulation optimization approach centred around a queuing network model of the logistic process of interest. We emphasize the power of grid computing for the simulation optimization studies and we design and implement an algorithm for distributing the computational load to parallel processors. Performance of the algorithm is demonstrated numerically using real-sized problem instances.
Scheda della pubblicazione: https://iris.univpm.it/handle/11566/253217