量子免疫克隆多目标优化算法

李阳阳; 焦李成

doi:10.3724/SP.J.1146.2006.01709

量子免疫克隆多目标优化算法

doi: 10.3724/SP.J.1146.2006.01709

基金项目:

国家自然科学基金(60703108)，国家863计划(2006AA01Z107)，国家 973项目 (2006CB705700)和陕西省自然科学基金(2007F32)资助课题

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出版历程
- 收稿日期: 2006-11-02
- 修回日期: 2007-05-15
- 刊出日期: 2008-06-19

Quantum-Inspired Immune Clonal Multiobjective Optimization Algorithm

摘要

摘要: 该文基于免疫系统的免疫优势概念和抗体克隆选择学说,采用量子位编码,提出了一种量子免疫克隆多目标优化算法,并对算法进行了理论分析;与RWGA、SPEA和MISA等算法的比较表明,该算法对低维多目标优化问题更有效。
- 人工免疫系统; 量子位编码; 多目标优化
Abstract: Based on the concept of immunodominance,antibody clonal selection theory and quantum bit strategy, a Quantum-inspired Immune Clonal Multiobjective Optimization Algorithm(QICMOA)is proposed.The QICMOA is compared with RWGA,SPEA and MISA in solving low-dimensional problems.The statistical results show that QICMOA has a good performance in converging to true Pareto-optimal fronts with a good distribution.

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参考文献(1)

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