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

An Adaptive Large Neighborhood Search for Relocating Vehicles in Electric Carsharing Services / Bruglieri, Maurizio; Pezzella, Ferdinando; Pisacane, Ornella. - (2017), pp. 632-634. (Intervento presentato al convegno The 12th edition of the Metaheuristics International Conference (MIC 2017) and the XII Metaheurísticas, Algoritmos Evolutivos y Bioinspirados (MAEB 2017) tenutosi a Barcellona, Spagna nel 4-7, Luglio, 2017).

An Adaptive Large Neighborhood Search for Relocating Vehicles in Electric Carsharing Services

Ferdinando Pezzella;Ornella Pisacane
2017-01-01

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
2017
978-84-697-4275-1
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11566/253692
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