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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 multi-objective optimization problem of V-belt drive, a Multi-Objective Differential Evolut ion Based on Gauss Mutation (GMODE) algorithm is proposed based on Gaussian mutation. This algorithm firstly introduces the good point set method to initialize the population. Secondly, when the difference vector is not suitable, Gaussian mutation is used to guide the individual to non-inferior solution evolution and improve the convergence speed of the algorithm. Finally, , Using Gaussian mutation, in order to enhance the ability of individuals to flee the local optimum. By comparing with other algorithms, it is found that the proposed algorithm can effectively avoid / premature convergence and has good convergence speed and diversity.