基于趋利避害原则的粒子群算法研究

Research on particle swarm optimizing algorithm based on seek advantage and avoid disadvantage principle

针对标准粒子群算法进行多极点函数优化时易导致早熟收敛及陷入局部最优的问题,把生物学中昆虫生存的趋利避害原则引入到粒子群优化算法中,改变传统粒子群优化算法只存在趋利操作而没有避害操作的单向性,提出了两种不同的保持或增加种群多样性的改进算法。仿真实验结果表明,与传统粒子群优化算法相比,采用基于趋利避害原则的粒子群算法处理复杂的多峰函数可显著提高算法的全局寻优性能。

To get rid of resulting in premature convergence and plunging into local optimum for standard particle swarm optimization to solve multiple-order pole functions,this paper introduced seek advantage and avoid disadvantage principle of some insects in biology into particle swarm optimization algorithm to change the single direction characteristic of the traditional algorithm which only had drawing on advantage operation instead of avoiding disadvantage operation.It proposed both kinds of ameliorated algorithms to maintain or increase population diversity.Simulation experiment results indicate that the particle swarm optimization based on seek advantage and avoid disadvantage principle can prominently improve the global optimization ability of the algorithm when dealing with complicated multimodal functions.