DocumentCode :
1781609
Title :
A hybrid metaheuristic for the Vehicle Routing Problem with Time Windows
Author :
Hifi, Mhand ; Lei Wu
Author_Institution :
UR EPROAD, Univ. de Picardie Jules Verne, Amiens, France
fYear :
2014
fDate :
3-5 Nov. 2014
Firstpage :
188
Lastpage :
194
Abstract :
In this paper we propose to solve the Vehicle Routing Problem with Time Windows (VRPTW) using a hybrid metaheuristic. The VRPTW is a bi-objective optimization problem where both the number of vehicles and the distance of the travel to use should be minimized. Because it is often difficult to optimize both objectives, we propose an approach that optimizes the distance traveled by a fleet of vehicles. Such a strategy has been already used by several authors in the domain. Herein, an instance of VRPTW is considered as the composition of the Assignment Problem and a series of Traveling Salesman Problems with Time Windows (TSPTW). Both AP and TSPTW are solved by using an ant colony optimization system. Furthermore, in order to enhance the quality of the current solution, a large neighborhood search is introduced. Finally, a preliminary experimental part is presented where the proposed method is evaluated on a set of benchmark instances and its results are compared to the best results obtained by the methods available in the literature. Our preliminary results show that the proposed hybrid method remains competitive and it is able to reach new minimum distances for some tested instances.
Keywords :
ant colony optimisation; search problems; travelling salesman problems; vehicle routing; TSPTW; VRPTW problem; ant colony optimization; bi-objective optimization problem; hybrid metaheuristic; neighborhood search; traveling salesman problems with time windows; vehicle routing problem with time windows; Ant colony optimization; Buildings; Optimization; Routing; Runtime; Vehicle routing; Vehicles; Ant colony; neighborhood search; vehicle routing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Control, Decision and Information Technologies (CoDIT), 2014 International Conference on
Conference_Location :
Metz
Type :
conf
DOI :
10.1109/CoDIT.2014.6996891
Filename :
6996891
Link To Document :
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