Homotopy-Inspired Cat Swarm Algorithm for Global Optimization

Abstract:

Based on the concepts of homotopy, a novel cat swarm algorithm, called a homotopy-inspired cat swarm algorithm (HCSA),is proposed to deal with the problem of global optimization. Proceeding from dependent variables of optimized function,it traces a path from the solution of an easy problem to the solution of the given one by use of a homotopy--|a continuous transformation from the easy problem to the given one.This novel strategy enables the cat swarm algorithm (CSA) to improve the search efficiency. Theoretical analysis proves that HCSA converges to the global optimum. Experimenting with a wide range of benchmark functions, we show that the proposed new version of CSA, with the continuous transformation, performs better, or at least comparably, to classic CSA.

• Periodical: Advanced Materials Research (Volumes 602-604)
• Pages: 1793-1797
• DOI: https://doi.org/10.4028/www.scientific.net/AMR.602-604.1793
• Online since: December 2012
• Authors: Shi Da Yang, Ya Lin Yi, Yan Ping Lu
• Keywords: Cat Swarm Algorithm, Global Optimization, Homotopy, Meta-Heuristic Algorithms

References

[1] Shu-Chuan Chu, Pei-wei Tsai, Jeng-Shyang Pan. Computational intelligence based on the behavior of cats. International Journal of Innovative Computing, Information and Control, Vol.3, 2007,p.163–173.

[2] Shyan-Shiou Chen. Chaotic Simulated Annealing by a Neural Network with a Variable Delay: Design and Application. IEEE transactions on neural networks, Vol.22, No.10, october 2011,pp.1557-1565.

DOI: 10.1109/tnn.2011.2163080

[3] Lin Zhou, Yan Chen, Ke Guo, Fangcheng Jia. New Approach for MPPT Control of Photovoltaic System With Mutative-Scale Dual-Carrier Chaotic Search. IEEE transactions on power electronics, Vol. 26, No. 4, april 2011.pp.1038-1048.

DOI: 10.1109/tpel.2010.2078519

[4] Shihao Ji, Layne T. Watson, Lawrence Carin. Semisupervised Learning of Hidden Markov Models via a Homotopy Method, IEEE transactions on pattern analysis and machine intelligence,Vol.31,No.2,February 2009.pp.275-287.

DOI: 10.1109/tpami.2008.71

[5] Irina Ciornei, and Elias Kyriakides. Hybrid Ant Colony-Genetic Algorithm (GAAPI)for Global Continuous Optimization. IEEE transactions on systems,man,and cybernetics-part B:cybernetics, accepted.

DOI: 10.1109/tsmcb.2011.2164245

[6] Wei-Chang Yeh. Optimization of the Disassembly Sequencing Problem on the Basis of Self-Adaptive Simplified Swarm Optimization. IEEE transactions on systems,man,and cybernetics-part A: systems and humans, Vol. 42, No. 1,January 2012.pp.250-261.

DOI: 10.1109/tsmca.2011.2157135