摘要
为研究V带传动多目标优化问题,基于高斯变异提出一种高斯变异多目标差异演化算法(Multi-Objective Differential Evolut ion Based on Gauss Mutation,GMODE)。该算法首先引入了佳点集方法对种群进行初始化,其次在差分向量选择不合适时,采用高斯变异,引导个体向非劣解进化,提高算法的收敛速度;最后在个体多次不更新位置时,采用高斯变异,以提升个体逃离局部最优点的能力。通过与其他算法的比较,发现该算法能有效避免/早熟0收敛,具有较好的收敛速度和多样性。
In order to study the V - belt Transmission multi - objective optimization problem, multi - objective differential evolution algorithm based on Gauss Mutation （GMODE） is proposed. The initial population is carried out based on good - point - set method, and in the processing of evolution, the gauss mutation is incorporated into differ- ential evolution when the difference vector inappropriate choice and individual stagnant evolution. The proposed algo- rithm is compared with several other evolutionmT algorithms, the results showed that the proposed algorithm could over- come the premature convergence efficiently and had better convergence and diversity metrics.
出处
《机械传动》
CSCD
北大核心
2013年第10期86-90,共5页
Journal of Mechanical Transmission
基金
河南省高等学校青年骨干教师资助计划项目(2011GGJS_296)
关键词
V带传动
多目标优化
差异演化算法
高斯变异
V- belt transmission Multi - objective optimization Differential evolution algorithm Gaussmutation
