摘要
针对现有供应商参与下的产品设计方法在零部件优化方面所存在的缺陷,提出了基于多目标优化的方法。以零部件的质量、成本和交货期为输入数据,构建了产品方案的多目标优化模型。基于Epsilon策略改进第二代非支配排序遗传算法后对优化模型进行求解,并获得了产品方案的Pareto前沿。以供应商参与下的数控机床研发问题为实例,进行仿真计算,结果表明所提出方法是可行的。
Aiming at limitations about components optimization existing in supplier involved product by the traditional optimization design, a novel multiobjective optimization method was proposed. Multiobjective optimization model was built based on import data of quality, cost and delivery time. Epsilon strategy was adopted to enhance improved non-dominated sorting genetics algorithm, and then the enhanced algorithm was employed to solve above mentioned model and to get finite Pareto solutions. Through simulation and computation of product supplier involved development of numerical control machine equipment illustrates the application and validation of the proposed method. [ Ch ,3 fig. 1 tab. 10 ref. ]
出处
《轻工机械》
CAS
2012年第2期86-89,共4页
Light Industry Machinery
