DocumentCode :
3096183
Title :
A genetic-based optimization for multi-depot vehicle routing problems
Author :
Tang, K.S. ; Yin, J.J. ; Man, K.F.
Author_Institution :
City Univ. of Hong Kong, Hong Kong, China
fYear :
2010
fDate :
4-7 July 2010
Firstpage :
1545
Lastpage :
1549
Abstract :
Multi-depot vehicle routing problem (MDVRP) is well-known as a combinatorial optimization problem and it is NP-completed. Existing methods are commonly heuristics, and hence the solutions are suboptimal. In this paper, with a novel design of chromosome structure, a multiple objective genetic algorithm is proposed to tackle with this problem, such that two objectives, namely the total travel distances and total travel time, are to be minimized. The effectiveness of the algorithm is demonstrated with simulation results. Moreover, its uses in real-world applications based on the support of geographical information are also briefly discussed.
Keywords :
combinatorial mathematics; computational complexity; genetic algorithms; transportation; vehicles; NP-completed; chromosome structure; combinatorial optimization problem; genetic-based optimization; heuristics; multidepot vehicle routing problem; multiple objective genetic algorithm; Biological cells; Genetics; Industrial electronics; Optimization; Routing; Search problems; Vehicles;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Industrial Electronics (ISIE), 2010 IEEE International Symposium on
Conference_Location :
Bari
Print_ISBN :
978-1-4244-6390-9
Type :
conf
DOI :
10.1109/ISIE.2010.5636289
Filename :
5636289
Link To Document :
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