A Novel Optimization Algorithm based on the Natural Behavior of the Ant Colonies | Zendy

Jiraporn Kiatwuthiamorn | Zendy; Arit Thammano | Zendy

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A Novel Optimization Algorithm based on the Natural Behavior of the Ant Colonies

Author(s) -

Jiraporn Kiatwuthiamorn,

Arit Thammano

Publication year - 2013

Publication title -

procedia computer science

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.334

H-Index - 76

ISSN - 1877-0509

DOI - 10.1016/j.procs.2013.09.244

Subject(s) - computer science , benchmark (surveying) , ant colony optimization algorithms , metaheuristic , foraging , mathematical optimization , optimization algorithm , swarm intelligence , parallel metaheuristic , algorithm , meta optimization , artificial intelligence , particle swarm optimization , mathematics , ecology , geodesy , biology , geography

Optimization problem is one of the most challenging problems that has received considerable attention over the last decade. Many metaheuristic methods have been proposed and successfully applied to find the optimal solution. Each technique has its good and bad points. A new optimization technique based on the natural behavior of the ant colonies is proposed in this paper. In this proposed algorithm, the foraging behavior of worker ants is employed for locally searching for better solution while the marriage, breeding, and feeding behaviors are used in reproduction of the new generation. The proposed algorithm has been evaluated on several benchmark problems. The experimental results demonstrate the effectiveness of the proposed algorithm

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