带有混沌变异的双种群伪并行PSO-DE混合算法

在求解全局优化问题时，采用单个PSO、DE算法有一定的不足，为了弥补这些不足，给出一种带有混沌变异的双种群伪并行PSO-DE混合算法（MPSODE）。通过对六个标准测试函数进行测试，结果表明，该混合算法是一种鲁棒性较强、求解精度高、收敛速度快的全局优化算法。

Dual Population With Chaotic Mutation Pseudo- Paralld PSO- DE Hybrid Algorithm

algorithms. researched Differential evolution and particle swarm optimization are two simple and efficient intelligent evolutionary A PSO -DE hybrid algorithm with chaotic mutation and pseudo parallel double populations problem is in this dissertation, to solve unconstrained optimization problems. The corresponding numerical simula tion results show that the proposed algorithms performance excellently. An initial population of uniform distribution is generated by using the chaotic motion and the premature populations are mutated by chaos, so as to enhance the ability of global optimization. Based on dual populations＇ evolutionary strategy, individuals of a population is e volved by the particle swarm optimization （ PSO）, individuals of another population is evolved by DE algorithm. In addition, using an information sharing mechanism is used so that individuals of the two populations can achieve co -evolution, for a modified dual populations hybrid algorithm based on PSO and DE.