Improved ant agents system by the dynamic parameter decision

Research output: Contribution to conferencePaperpeer-review

8 Citations (Scopus)

Abstract

Ant Colony System(ACS) Algorithm is a new metaheuristic for hard combinational optimization problem. It is a population-based approach that uses exploitation of positive feedback as well as greedy search. It was first proposed for tackling the well known Traveling Salesman Problem(TSP). In this paper, we introduce a new version of the ACS based on Dynamic weighted updating method and Dynamic ant number decision method using curve fitting algorithm. Implementation to solve TSP and the performance results under various conditions are conducted, and the comparison between the original ACS and the proposed method is shown. It turns out that our proposed method can compete with the original ACS in terms of solution quality and computation speed to these problems.

Original languageEnglish
Pages666-669
Number of pages4
Publication statusPublished - 2001
Event10th IEEE International Conference on Fuzzy Systems - Melbourne, Australia
Duration: 2 Dec 20015 Dec 2001

Conference

Conference10th IEEE International Conference on Fuzzy Systems
Country/TerritoryAustralia
CityMelbourne
Period2/12/015/12/01

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