文章基本信息

标题：Optimizing Large Scale Combinatorial Problems Using Multiple Ant Colonies Algorithm Based on Pheromone Evaluation Technique
作者：Alaa Aljanaby ; Ku Ruhana Ku Mahamud ; Norita Md. Norwawi 等
期刊名称：International Journal of Computer Science and Network Security
印刷版ISSN：1738-7906
出版年度：2008
卷号：8
期号：10
页码：54-58
出版社：International Journal of Computer Science and Network Security
摘要：The approach of using multiple ant colonies is an extension of the Ant Colony Optimization framework. It offers a good chance to improve the performance of the ant algorithms by encouraging the exploration of a wide area of the search space without losing the chance of exploiting the history of the search. In this paper a new multiple ant colonies optimization algorithm is proposed. The new algorithm is based on the ant colony system and utilizes average and maximum pheromone evaluation mechanisms. The new algorithm can effectively be used to tackle large scale optimization problems. Computational tests show promises of the new algorithm.
关键词：Ant Colony Optimization; Meta-heuristic Algorithms; Combinatorial optimization problems