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A hybrid genetic algorithm for the vehicle routing problem withthree-dimensional loading constraints

Published online by Cambridge University Press:  15 May 2012

Lixin Miao ,
Qingfang Ruan ,
Kevin Woghiren  and
Qi Ruo
Lixin Miao
Affiliation:
Research Center for Modern Logistics, Graduate School at Shenzhen, Tsinghua University, 518055 Shenzhen, P.R. China. [email protected], [email protected], [email protected]
Qingfang Ruan
Affiliation:
Research Center for Modern Logistics, Graduate School at Shenzhen, Tsinghua University, 518055 Shenzhen, P.R. China. [email protected], [email protected], [email protected]
Kevin Woghiren
Affiliation:
HSBC Business School, Graduate School at Shenzhen, Peking University, 518055 Shenzhen, P.R. China; [email protected]
Qi Ruo
Affiliation:
Research Center for Modern Logistics, Graduate School at Shenzhen, Tsinghua University, 518055 Shenzhen, P.R. China. [email protected], [email protected], [email protected]
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Abstract

This paper addresses a Three-Dimensional Loading Capacitated Vehicle Routing Problem(3L-CVRP) which combines a three-dimensional loading problem and vehicle routing problemin distribution logistics. The problem requires the combinatorial optimization of afeasible loading solution and a successive routing of vehicles to satisfy client demands,where all vehicles must start and terminate at a central depot. In spite of its clearpractical significance in the real world of distribution management, 3L-CVRP in literatureis very limited for its high combinatorial complexity. We solve this problem by a hybridapproach which combines Genetic Algorithm and Tabu Search (GATS). Genetic algorithm isdeveloped for vehicle routing and tabu search for three-dimensional loading, while thesetwo algorithms are integrated for the combinatorial problem. We computationally evaluatethis hybrid genetic algorithm on all publicly available test instances, and obtain newbest solutions for several instances.

Keywords

Vehicle routingthree-dimensional loadinggenetic algorithmtabu search
Type
Research Article
Information
RAIRO - Operations Research , Volume 46 , Issue 1 , January 2012 , pp. 63 - 82
Copyright
© EDP Sciences, ROADEF, SMAI, 2012

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