Volume 46, Number 1, January-March
|Page(s)||63 - 82|
|Published online||15 May 2012|
A hybrid genetic algorithm for the vehicle routing problem with three-dimensional loading constraints
Research Center for Modern Logistics, Graduate School at Shenzhen,
Tsinghua University, 518055
email@example.com, firstname.lastname@example.org, email@example.com
2 HSBC Business School, Graduate School at Shenzhen, Peking University, 518055 Shenzhen, P.R. China
Accepted: 2 April 2012
This paper addresses a Three-Dimensional Loading Capacitated Vehicle Routing Problem (3L-CVRP) which combines a three-dimensional loading problem and vehicle routing problem in distribution logistics. The problem requires the combinatorial optimization of a feasible 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 clear practical significance in the real world of distribution management, 3L-CVRP in literature is very limited for its high combinatorial complexity. We solve this problem by a hybrid approach which combines Genetic Algorithm and Tabu Search (GATS). Genetic algorithm is developed for vehicle routing and tabu search for three-dimensional loading, while these two algorithms are integrated for the combinatorial problem. We computationally evaluate this hybrid genetic algorithm on all publicly available test instances, and obtain new best solutions for several instances.
Mathematics Subject Classification: 97M40
Key words: Vehicle routing / three-dimensional loading / genetic algorithm / tabu search
© EDP Sciences, ROADEF, SMAI, 2012
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