摘要
针对加工参数优化过程中粒子群优化算法的优化效果受参数影响较大的问题,提出了自适应协同粒子群优化算法。对粒子群优化算法的参数对优化结果的影响进行了详细而深入的分析,在此基础上,给出了优化过程中惯性权重、学习因子、最大速度等参数的变化规律,并通过仿真的方法确定了最优参数的取值。最后通过对基准函数的仿真实验,验证了本文算法的正确性和有效性。
The optimization effect is affected by the parameters in particle swarm optimization algorithm in the process of machine parameters optimization, the adaptive collaborative particle swarm optimization algorithm was proposed. The in- fluence of parameters on the optimization results of particle swarm optimization algorithm was analyzed detailedly and deep- ly. It gives parameters such as inertia weight, learning factor, maximum speed in the optimization process, and the simula- tion method to determine the optimal values of the parameters. Finally the simulation experiment of benchmark function is hold to verify the correctness and effectiveness of the algorithm in this paper.
出处
《工具技术》
2014年第4期21-24,共4页
Tool Engineering
基金
国家高技术研究发展计划(863计划)资助项目(SS2012-AA041303)
关键词
加工参数优化
优化算法
粒子群算法
自适应协同粒子群
machine parameter optimization
optimization algorithm
particle swarm optimization
adaptive collaborative PSO
