J4 ›› 2011, Vol. 46 ›› Issue (9): 106-111.
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刘衍民
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贵州教育厅社科项目(0705204,102(07));遵市科技局项目(［2008］21)
LIU Yan-min
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摘要：
为有效求解带有约束条件的优化问题,提出一种动态多种群粒子群算法。采用动态多种群策略和广泛学习策略来提升种群的多样性, 并根据人类社会“人尽其才”的思想, 为每个子群指派成员, 以发挥每个粒子的最大效用。采用动态变异策略, 对全局最优粒子(Gbest)进行变异操作以提升算法跳出局部最优解的能力。在基准函数的测试结果中显示DMCPSO获得了较高的求解精度。
关键词: 约束优化;动态多种群;粒子群算法
Abstract:
In order to solve constrained optimization problem, a dynamic multi-swarm particle swarm optimizer (DMCPSO) is proposed. In DMCPSO, dynamic multi-swarms and comprehensive learning strategy are applied to improve the swarm diversity. On the basis of the idea “no talent is to be wasted” from human society, each sub-swarm selects its member to the maximum utility of each particle, and the dynamic mutation operator is adopted for best performing particle (Gbest) to improve the ability of escaping from local optima. Experimental simulation results of benchmark functions show that DMCPSO achieves better solutions than other algorithms.
Key words: constrained optimization; dynamic multiswarm; particle swarm optimizer
刘衍民. 求解约束优化问题的动态多种群粒子群算法[J]. J4, 2011, 46(9): 106-111.
LIU Yan-min. Dynamic multi-swarm particle swarm optimizer for constrained optimization problems[J]. J4, 2011, 46(9): 106-111.
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http://lxbwk.njournal.sdu.edu.cn/CN/Y2011/V46/I9/106
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