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A policy of conflict negotiation based on fuzzy matter element particle swarm optimization in distributed collaborative creative design

机译:分布式协同创新设计中基于模糊物元粒子群优化的冲突协商策略。

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摘要

A novel negotiation algorithm of swarm global exploration, based on Fuzzy Matter Element Particle Swarm Optimization (FMEPSO), is presented to resolve the conflicts in complex product distributed collaborative creative design systems. Firstly, an extensive formalized expression of conflicts in the fuzzy matter element model is given, next, the fuzzy matter element optimization method (FMEOM) is used to change the multi-object negotiation problems to single-object negotiation problems, and the regularized correlation function is regarded as the fitness function judging the stand and fall of particle; Then, in the implementation process of the PSO algorithm, the mutation mechanics is introduced to mutate the inactive particle and the particle with the smallest fitness according to mutation probability, which can not only effectively solve the premature convergence problem, but also significantly speed up the convergence; Finally, an example of the parameter optimization design in a power train is used to show the validity of this algorithm.
机译:提出了一种基于模糊物元粒子群优化(FMEPSO)的群全局探索协商算法,以解决复杂产品分布式协同创意设计系统中的冲突。首先,给出了模糊物元模型中冲突的广义形式化表达,其次,使用模糊物元优化方法(FMEOM)将多对象谈判问题变为单对象谈判问题,并利用正则相关函数被认为是判断粒子的落差的适应度函数;然后,在PSO算法的实现过程中,引入了突变机制,根据突变概率对不活跃粒子和适应度最小的粒子进行了突变,不仅可以有效地解决过早收敛的问题,而且可以显着加快算法的收敛速度。收敛;最后,以动力总成参数优化设计为例,验证了该算法的有效性。

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