Convergence Proof of a Class of Adaptive Ant Colony Algorithm

DOI

10.2991/iccmcee-15.2015.182How to use a DOI?

Keywords

Ant colony optimization, markov process, convergence

Abstract

This paper presents a class of adaptive ant colony optimization algorithm and proves its convergence properties. The global searching and convergence ability are improved by adaptively changing the pheromone trails evaporation factors and decreasing lower pheromone bound. Markov process analysis is used to prove convergence properties of the algorithms. It is shown that its current solutions of the system converge, with probability one, to an optimal solution of the system.

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  - BaoJiang Zhao
PY  - 2015/11
DA  - 2015/11
TI  - Convergence Proof of a Class of Adaptive Ant Colony Algorithm
BT  - Proceedings of the 2015 4th International Conference on Computer, Mechatronics, Control and Electronic Engineering
PB  - Atlantis Press
SP  - 969
EP  - 972
SN  - 2352-5401
UR  - https://doi.org/10.2991/iccmcee-15.2015.182
DO  - 10.2991/iccmcee-15.2015.182
ID  - Zhao2015/11
ER  -