Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)

Convergence Analysis for Generalized Ant Colony Optimization Algorithm

Authors
Daiyuan Zhang1
1Nanjing University of Posts and Telecommunications
Corresponding Author
Daiyuan Zhang
Available Online December 2008.
DOI
10.2991/jcis.2008.97How to use a DOI?
Keywords
artificial intelligence, ant colony optimization, ant algorithms, convergence proof, approximation algorithms, GACO algorithm.
Abstract

A new algorithm is proposed, which is called Generalized Ant Colony Optimization (GACO) algorithm. Two new functions are presented to model the behavior for describing the pheromone evaporation and pheromone added to the edges that belong to the best-so-far solution. A class of strictly increasing function is proposed, which gives a general form of expression for the probability of selecting the next node. An important theorem is proved for describing the convergence of GACO algorithm, i.e. for a sufficiently large number of algorithm iterations, the probability of finding the globally optimal solution at least once tends to 1.

Copyright
© 2008, 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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Volume Title
Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
Series
Advances in Intelligent Systems Research
Publication Date
December 2008
ISBN
10.2991/jcis.2008.97
ISSN
1951-6851
DOI
10.2991/jcis.2008.97How to use a DOI?
Copyright
© 2008, 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  - Daiyuan Zhang
PY  - 2008/12
DA  - 2008/12
TI  - Convergence Analysis for Generalized Ant Colony Optimization Algorithm
BT  - Proceedings of the 11th Joint Conference on Information Sciences (JCIS 2008)
PB  - Atlantis Press
SP  - 578
EP  - 583
SN  - 1951-6851
UR  - https://doi.org/10.2991/jcis.2008.97
DO  - 10.2991/jcis.2008.97
ID  - Zhang2008/12
ER  -