多目标优化中带变异算子的灰色粒子群算法-计算机工程与应用.PDFVIP

140 2012 ，48 （34） Computer Engineering and Applications 计算机工程与应用 多目标优化中带变异算子的灰色粒子群算法 彭耶萍，董坚峰 PENG Yeping, DONG Jianfeng 吉首大学 软件学院，湖南 张家界 427000 Software College, Jishou University, Zhangjiajie, Hunan 427000, China PENG Yeping, DONG Jianfeng. Grey particle swarm algorithm with mutation operator in multi-objective optimization. Computer Engineering and Applications, 2012, 48 （34 ）：140-143. Abstract ：A particle swarm algorithm based on mutation operator is put forward for getting better Pareto solution sets in the field of multi-objective optimization problem. The grey correlation degree theory, which is introduced by variance, is applied to the algorithm for distinguishing the sequences with equal means but sensible difference of ob- ject position correlation coefficients. The particle swarm algorithm is controlled by this mutation strategy. Hence, the local convergence phenomenon is prevented during solving multi-objective problem with grey particle swarm algorithm. The algorithm ’s performance is tested by four groups of different types of benchmark functions. It shows that the algorithm can not only convergence to the Pareto optimal solution sets very well but also efficiently avoid falling into the local optimal solution too early. Key words ：multi-objective; mutation operator; grey relational degree; Particle Swarm algorithm; optimization 摘 要：针对如何在多目标优化过程中求解更好的Pareto 解集，提出一种基于变异算子的灰色粒子群算法。该 算法将灰色关联度应用于粒子群算法，且将方差的概念引入灰色关联度，以区分那些点关联系数有显著差异 而其均值相等的各组序列。以此作为变异策略来控制粒子群算法，以避免现有灰色粒子群算法在求解多目标 问题时所出现的局部收敛现象。通过四组不同类型的基准函数测试算法性能，测试结果表明该算法能很好地 收敛到Pareto 最优解集并有效避免了过早陷入局部最优解。 关键词：多目标；变异算子；灰色关联度；粒子群算法；优化 文献标识码：A 中图分类号：TP311 doi ：10.3778/j.issn. 1002-8331.1105-0207 1 引言 多目标优化问题主要特点是各目标之间的相互 多目标优化问题（Multi-Objective optimization 矛盾性使得问题不可能存在单个绝对最优解，而是 [1] 一个矛盾目标集。在多目标优化问题中，最优解通 problems ，MOPS ）是一类普遍存在的优化问题，其