A genetic-based optimization for multi-depot vehicle routing problems

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review

2 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Title of host publicationIEEE International Symposium on Industrial Electronics
Pages1545-1549
Publication statusPublished - 2010
Externally publishedYes

Conference

Title2010 IEEE International Symposium on Industrial Electronics, ISIE 2010
PlaceItaly
CityBari
Period4 - 7 July 2010

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. © 2010 IEEE.

Citation Format(s)

A genetic-based optimization for multi-depot vehicle routing problems. / Tang, K. S.; Yin, J. J.; Man, K. F.
IEEE International Symposium on Industrial Electronics. 2010. p. 1545-1549 5636289.

Research output: Chapters, Conference Papers, Creative and Literary WorksRGC 32 - Refereed conference paper (with host publication)peer-review