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。
Abstract
In order to study the V-belt Transmission multi-objective optimization problem
multi-objective differential evolut ion algorithm based on Gauss Mutation( GMODE) is proposed. The init ial population is carried out based on good-point-set method
and in the processing of evolution
the gauss mutation is incorporated into differential evolut ion when the difference vector inappropriate choice and individual stagnant evolution. The proposed algorithm is compared with several other evolutionary algorithms
the results showed that the proposed algorithm could overcome the premature convergence efficiently and had better convergence and diversity metrics.