一种改进的粒子群优化算法惯性权值递减策略

摘要

结合粒子群优化( PSO)算法的特点,分析惯性权值的关键性作用. 在此基础上提出一种改进的非线性惯性权值递减策略. 同时利用两种基准函数对该策略进行测试. 实验结果表明,在参数设置均相同的条件下,改进后的权值递减策略在算法迭代初期具有较好的多样性,有利于跳出局部极值,在迭代后期具有更好的全局寻优能力. 当维数不变时,随着种群规模以及最大迭代次数的相应增加,改进后的权值递减策略在收敛精度指标上要明显优于对比算法.%Combining with the particle swarm optimization ( PSO) algorithm characteristics ,it analyzed the key role of inertia weight in this paper .The improved nonlinear inertia weight decreasing strategy was pro-posed on this basis .Simultaneously the strategy was tested by applying two reference functions .The exper-imental results showed that the improved strategy is endowed better diversity in the initial stage of the al -gorithm,it is advantageous to get rid of the affect of the local extremum and enjoys better global optimiza -tion ability in the later iterations on the same condition .When the dimension unchanged and with the ad-dition of population size and the maximum number of iterations ,the improved nonlinear inertia weight de-creasing strategy is superior to the contrast algorithm in the convergence precision .