An Improved GA for solving multiple depot VRP
Authors
Yudong Zhang, Genlin Ji, Shuihua Wang, Preetha Phillips, William Wang, Elizabeth Lee
Corresponding Author
Yudong Zhang
Available Online March 2015.
- 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/).
Cite this article
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 -