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Modified binary particle swarm optimization |
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| Authors: | Sangwook Lee Sangmoon Soak Sanghoun Oh Witold Pedrycz Moongu Jeonc |
| Institution: | a) College of Computing, Georgia Institute of Technology, Atlanta, GA 30332, USA; b) Information Systems Examination Team, Korean Intellectual Property Office (KIPO), Gov. Complex Daejeon Bldg.4 920 Dunsandong, Seogu, Republic of Korea; c) Department of Information and Communications, Gwangju Institute of Science and Technology, 261 Cheomdan-gwagiro, Buk-gu, Gwanju, Republic of Korea; d) Department of Electrical & Computer Engineering, University of Alberta, Edmonton, AB, Canada |
| Abstract: | This paper presents a modified binary particle swarm optimization (BPSO) which adopts concepts of the genotype-phenotype representation and the mutation operator of genetic algorithms. Its main feature is that the BPSO can be treated as a continuous PSO. The proposed BPSO algorithm is tested on various benchmark functions, and its performance is compared with that of the original BPSO. Experimental results show that the modified BPSO outperforms the original BPSO algorithm. |
| Keywords: | Binary particle swarm optimization Genotype-phenotype Mutation |
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