A novel meta-heuristic optimization algorithm: current search

Authors:
Anusorn Sakulin;Deacha Puangdownreong
Affiliations:
Department of Electrical Engineering, Faculty of Engineering, South-East Asia University, Bangkok, Thailand;Department of Electrical Engineering, Faculty of Engineering, South-East Asia University, Bangkok, Thailand
Venue:
AIKED'12 Proceedings of the 11th WSEAS international conference on Artificial Intelligence, Knowledge Engineering and Data Bases
Year:
2012

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Abstract

Inspired by an electric current flowing through electric networks, a novel meta-heuristic optimization algorithm named the Current Search (CS) is proposed in this article. The proposed CS algorithm is an optimization algorithm based on the intelligent behavior of electric current flowing through open and short circuits. To perform its effectiveness and robustness, the proposed CS algorithm is tested against five wellknown benchmark continuous multivariable test functions collected by Ali et al. The results obtained by the proposed CS are compared with those obtained by the popular search techniques widely used to solve optimization problems, i.e., Genetic Algorithm (GA), Particle Swarm Optimization (PSO), and Tabu Search (TS). The results show that the proposed CS outperforms other algorithms. The results obtained by the proposed CS are superior within reasonable time consumed.