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一种量化正交免疫克隆粒子群数值优化算法*

, PP. 583-592

Keywords: 粒子群优化,人工免疫系统,克隆选择,正交设计,进化计算

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Abstract:

为了解决粒子群算法收敛速度慢和早熟收敛等问题,根据生物免疫系统理论中的克隆选择学说,提出一种量化正交免疫克隆粒子群算法.给出正交子空间分割算法,并采用正交交叉策略来增强子代个体解分布的均匀性.为避免个体邻域内最优解的丢失,提出一种自学习算子,并证明该算法的全局收敛性.实验中对标准测试函数进行20~1000维的测试,分别与5种算法进行比较,并给出算法参数对计算复杂度的影响.结果表明,本文方法有效克服早熟收敛,并且在保持种群多样性的同时提高收敛速度.

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