Multi Colony Ant Model using Positive,Negative Interaction between Colonies


The KIPS Transactions:PartB , Vol. 10, No. 7, pp. 751-756, Dec. 2003
10.3745/KIPSTB.2003.10.7.751,   PDF Download:

Abstract

Ant Colony Optimization (ACO) is new meta heuristics method to solve hard combinatorial optimization problem. It is a population based approach that uses exploitation of positive feedback as well as greedy search. It was firstly proposed for tackling the well known Traveling Salesman Problem (TSP). In this paper, we introduce Multi Colony Ant Model that achieve positive interaction and negative interaction through Intensification and Diversification to improve original ACS performance. This algorithm is a method to solve problem through interaction between ACS groups that consist of some agent colonies to solve TSP problem. In this paper, we apply this proposed method to TSP problem and evaluates previous method and comparison for the performance. and we wish to certify that qualitative level of problem solution is excellent.


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Cite this article
[IEEE Style]
L. S. Gwan and J. T. Chung, "Multi Colony Ant Model using Positive,Negative Interaction between Colonies," The KIPS Transactions:PartB , vol. 10, no. 7, pp. 751-756, 2003. DOI: 10.3745/KIPSTB.2003.10.7.751.

[ACM Style]
Lee Seung Gwan and Jeong Tae Chung. 2003. Multi Colony Ant Model using Positive,Negative Interaction between Colonies. The KIPS Transactions:PartB , 10, 7, (2003), 751-756. DOI: 10.3745/KIPSTB.2003.10.7.751.