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Volume 30 Issue 10
Jan.  2011
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Cong Lin, Jiao Li-Cheng, Sha Yu-Heng. Orthogonal Immune Clone Particle Swarm Algorithm on Multiobjective Optimization[J]. Journal of Electronics & Information Technology, 2008, 30(10): 2320-2324. doi: 10.3724/SP.J.1146.2007.00566
Citation: Cong Lin, Jiao Li-Cheng, Sha Yu-Heng. Orthogonal Immune Clone Particle Swarm Algorithm on Multiobjective Optimization[J]. Journal of Electronics & Information Technology, 2008, 30(10): 2320-2324. doi: 10.3724/SP.J.1146.2007.00566

Orthogonal Immune Clone Particle Swarm Algorithm on Multiobjective Optimization

doi: 10.3724/SP.J.1146.2007.00566
  • Received Date: 2007-04-16
  • Rev Recd Date: 2007-10-08
  • Publish Date: 2008-10-19
  • Based on the particle swarm optimization and antibody clonal selection theory, a novel Orthogonal Immune Clone Particle Swarm Algorithm (OICPSO) is presented to solve multiobjective optimization. According to the problem characters, clone operator, immune gene operator and clone selection operator are designed in this paper. And discrete orthogonal crossover operator is used in immune gene operations to obtain uniformity of the objective space and the idea Pareto solutions. And crowding-comparison approach is adopted to obtain the uniformity of the population distribution. In experiments, the results of OICPSO are compared with NSGA-II and MOPSO, and the quality of solutions is analyzed with parameters. The results indicate that OICPSO not only can increase the solutions diversity but also can obtain the Pareto solutions. OICPSO is effective on multiobjective optimizations.
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