An adaptive hybrid ant colony optimization algorithm for solving Capacitated Vehicle Routing

DOI

10.2991/iiicec-15.2015.132How to use a DOI?

Keywords

Ant Colony Algorithm; Capacitated Vehicle Routing Problem; Genetic Algorithm; pheromone matrix

Abstract

Ant Colony Algorithm has certain advantages in solving Capacitated Vehicle Routing Problem (CVRP), but there are still easy to fall into local optimum, the search speed etc. To overcome these problems this paper presents an adaptive hybrid Ant colony optimization algorithm for solving Capacitated Vehicle Routing Problem. The adaptive hybrid ant colony optimization algorithm uses genetic algorithms to adjust pheromone matrix algorithm, and designs an adaptive pheromone evaporation rate adjustment strategies, and uses local search strategies to reduce the amount of calculation. Experiment on Some classic problems shows that the presented algorithm for solving the Capacitated Vehicle Routing Problem is effective and has better performance.

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  - YuZhong Peng
AU  - Yonghua Pan
AU  - ZhengYou Qin
AU  - DeYong Li
PY  - 2015/03
DA  - 2015/03
TI  - An adaptive hybrid ant colony optimization algorithm for solving Capacitated Vehicle Routing
BT  - Proceedings of the 2015 International Industrial Informatics and Computer Engineering Conference
PB  - Atlantis Press
SP  - 577
EP  - 580
SN  - 2352-538X
UR  - https://doi.org/10.2991/iiicec-15.2015.132
DO  - 10.2991/iiicec-15.2015.132
ID  - Peng2015/03
ER  -