An Improved GA for solving multiple depot VRP

DOI

10.2991/iiicec-15.2015.126How to use a DOI?

Keywords

Vehicle routing problem; genetic algorithm; fitness-scaling; local search

Abstract

Multi-depot vehicle routing problem is a NP-hard combinatorial optimization problem. In this paper, we proposed an improved genetic algorithm (GA), which combined GA with fitness-scaling and local search. The experiments compared the proposed approach with standard GA, simulated annealing, Tabu search, and particle swarm optimization. The results showed that the proposed method was superior to GA, SA, TS, and PSO,w.r.t.solution accuracy.

Copyright

© 2015, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Yudong Zhang
AU  - Genlin Ji
AU  - Shuihua Wang
AU  - Preetha Phillips
AU  - William Wang
AU  - Elizabeth Lee
PY  - 2015/03
DA  - 2015/03
TI  - An Improved GA for solving multiple depot VRP
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 551
EP  - 554
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.126
DO  - 10.2991/iiicec-15.2015.126
ID  - Zhang2015/03
ER  -