Parallel Ant Colony Optimization Algorithm for Vehicle Routing Problem

DOI

10.2991/icsecs-13.2013.22How to use a DOI?

Keywords

parallel; ant colony algorithm; premature stage

Abstract

this paper presents a parallel ant colony algorithm based on Message Passing Interface (MPI) for vehicle routing problem (VRP). At the beginning of the algorithm, a sub-colony is simulated in each processor which independently computes to ensure population diversity. In order to overcome the shortcoming of the ant colony algorithm that is easy to fall into local optimum, a method is designed to judge weather the parallel algorithm get into premature stage. Once premature phenomenon turns up in the whole colony, the local search strategy is used to help the algorithm search the better solution. When the iterative process is over, the optimal solution of all ant colony computed is improved by the neighborhood exchange strategy. Experimental results show that the algorithm is effective and feasible especially for the VRP of large scale cities.

Copyright

© 2013, 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  - Ya Li
AU  - Dong Wang
AU  - Yuewu Yang
AU  - Yan Zhou
AU  - Chen Wu
PY  - 2013/09
DA  - 2013/09
TI  - Parallel Ant Colony Optimization Algorithm for Vehicle Routing Problem
BT  - Proceedings of the 2013 International Conference on Software Engineering and Computer Science
PB  - Atlantis Press
SP  - 107
EP  - 111
SN  - 1951-6851
UR  - https://doi.org/10.2991/icsecs-13.2013.22
DO  - 10.2991/icsecs-13.2013.22
ID  - Li2013/09
ER  -