透镜成像反学习策略在粒子群算法中的应用

摘要

By introducing opposition-based learning (OBL) in PSO ,particles are enabled to find an opposite position that is closer to the global optimization solution .However ,OBL only makes a good performance on the initial phrase of the evolution , while at later stages it needs to be combined with other techniques (e .g .Cauchy mutation ) to improve its ability of“exploration” . In this paper ,a novel OBL based on the principle of lens imaging is proposed .It uses two parameters (i .e .,zoom factor and the factor of search radius ) ,which will achieve a better balance between PSO’s“exploration”and“exploitation”abilities .The simula-tion shows that the novel OBL possesses better convergence rate and convergence effect .%在PSO中引入反向学习策略（Opposite-Based Learning ）可使粒子在搜寻过程中总能找到当前解的反向位置，增加了接近全局最优解的机会。然而，OBL仅在演化初期作用显著，在演化后期则需通过变异等手段来提高其“开发”能力。针对该问题，基于透镜成像原理，引入缩放因子和搜索半径两个可调参数进一步平衡了算法的“探索”和“开发”能力。实验表明该策略能够提高种群多样性和收敛性能。