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Zbl 1026.90013
Baker, Barrie M.; Ayechew, M.A.
A genetic algorithm for the vehicle routing problem. (English)
[J] Comput. Oper. Res. 30, No.5, 787-800 (2003). ISSN 0305-0548

Summary: This study considers the application of a genetic algorithm (GA) to the basic vehicle routing problem (VRP), in which customers of known demand are supplied from a single depot. Vehicles are subject to a weight limit and, in some cases, to a limit on the distance travelled. Only one vehicle is allowed to supply each customer. The best known results for benchmark VRPs have been obtained using tabu search or simulated annealing. GAs have seen widespread application to various combinatorial optimisation problems, including certain types of vehicle routing problem, especially where time windows are included. However, they do not appear to have made a great impact so far on the VRP as described here. In this paper, computational results are given for the pure GA which is put forward. Further results are given using a hybrid of this GA with neighbourhood search methods, showing that this approach is competitive with tabu search and simulated annealing in terms of solution time and quality.

MSC 2000:: *90B20 Highway traffic
90C59 Approximation methods and heuristics

Keywords: routing; heuristics; genetic algorithms

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