DocumentCode :
657991
Title :
Optimization of the multi-depot & Multi-vehicle pickup and delivery problem with time windows using genetic algorithm
Author :
Ben Alaia, E. ; Dridi, I. Harbaoui ; Bouchriha, H. ; Borne, Pierre
Author_Institution :
LAGIS, Ecole Centrale de Lille, Villeneuve d´Ascq, France
fYear :
2013
fDate :
6-8 May 2013
Firstpage :
343
Lastpage :
348
Abstract :
In This paper we present a genetic algorithm (GA) for Multi-vehicle and multi-depots pickup and delivery problem with time windows (m-MDPDPTW). The m-MDPDPTW is a class of vehicles routing problem which must construct a set of routes in order to satisfy transportation requests, between the origins nodes (pickup customers) and the destination nodes (delivery customers), satisfying precedence, capacity and time constraints. Each load has to be transported by one of the vehicles, between pickup and delivery customers. We are assuming that all vehicles have the same capacity and each one start and finish route at the same depot. We present, in this paper, a brief literature review of the MDPDPTW and construct a mathematical model of the above problem. We present our approach based on genetic algorithms to give a set of feasible solutions to the m-MDPDPTW minimizing total travel distance.
Keywords :
genetic algorithms; mathematical analysis; vehicle routing; GA; delivery customers; destination nodes; genetic algorithm; m-MDPDPTW; mathematical model; multivehicle and multidepots pickup and delivery problem with time windows; origins nodes; pickup customers; time constraints; total travel distance minimization; transportation requests; vehicles capacity; vehicles load; vehicles routing problem; Genetic algorithms; Optimization; Routing; Sociology; Statistics; Vehicles; Genetic algorithm; Multi-depot vehicle routing problem; Time windows; pickup and delivery problem;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Decision and Information Technologies (CoDIT), 2013 International Conference on
Conference_Location :
Hammamet
Print_ISBN :
978-1-4673-5547-6
Type :
conf
DOI :
10.1109/CoDIT.2013.6689568
Filename :
6689568
Link To Document :
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