An improved chaotic ant colony algorithm

Authors:
Hongru Li;Shuzhuo Wang;Mengfan Ji
Affiliations:
College of Information Science and Engineering, Northeastern University, Shenyang, P.R. China;College of Information Science and Engineering, Northeastern University, Shenyang, P.R. China;College of Information Science and Engineering, Northeastern University, Shenyang, P.R. China
Venue:
ISNN'12 Proceedings of the 9th international conference on Advances in Neural Networks - Volume Part I
Year:
2012

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Abstract

Ant colony algorithm is a rising intelligent algorithm in recent years, which performs well in solving large-scale combinatorial optimization problem. On the basis of analyzing the advantages and disadvantages of ant colony algorithm, to solve the shortage of the basic ant colony algorithm, we present a chaotic ant swarm algorithm with strategy of return-trip optimization and elitist strategy. At first, make the basic ant colony algorithm into chaos initialization. When getting the mathematical solution, put into chaos interference factor to prevent from getting into the local minimum. Furthermore bring two improvement projects: strategy of return-trip optimization and elitist strategy into the ant colony algorithm to improve the quality of the solution. The simulation results indicate that the improved chaotic ant colony algorithm is a good solution to the shortages of the basic ant colony algorithm.