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 availableI documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.