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针对大规模定制下基于多平台的参数化产品族优化方法中,需要事先指定平台变量的不足,本文提出了一种多平台产品族双层多目标并行协同优化算法,用于求解多平台下参数化产品族多目标优化问题。仿真实验结果表明,所提方法能够允许在平台变量未知的情况下,通过在运行过程中自动改变平台共性,并搜索共性与产品差异性之间的最佳平衡点,经过一次优化过程即可选择平台变量和差异性变量的最佳配置,以及平台变量和差异性变量取值的最佳设置;与文献中其他方法相比,本文方法所得产品族优化设计方案整体性能更佳。
In order to solve the problem of multi-platform parametric product family optimization in mass customization, it is necessary to designate a platform variable in advance. In this paper, a multi-platform multi-platform multi-objective parallel collaborative optimization algorithm is proposed to solve the problem of multi- Multi-objective optimization of product family. The simulation results show that the proposed method can allow the optimization process to be changed automatically by changing the platform commonality and searching for the best balance between commonality and product differentiation when the platform variables are unknown. The optimal configuration of platform variables and variance variables, and the optimal settings of platform variables and variance variables. Compared with other methods in the literature, the optimized design of product family obtained by this method is better overall performance.