【摘要】 为减少产品开发过程中的返工迭代,提出一种基于设计结构矩阵(DSM)理论的多目标流程优化遗传算法.通过优化任务执行顺序,减少产品开发过程中的返工以压缩进度和降低成本.该优化算法是一种改进的遗传(GA)算法,在适应度函数中考虑了时间和费用两个指标;在选择、交叉、变异算子中采用了优解保持策略.仿真结果表明,对于高任务耦合度的产品开发项目,该优化算法能使开发时间压缩30%~40%,费用降低7%~20%.更多还原

【Abstract】 A multi-object scheduling algorithm based on design structure matrix(DSM) theory is presented for product development process optimization.It is an improved genetic algorithm which takes several measures to have the computation result effective,stable,and reliable.First,it takes account of multi-indicators,such as time and expenditure,in constructing fitness function.Second,several policies are adopted to retain good individuals in the group during the selection,crossover,and mutation process.Computation study results show that this optimization algorithm can effectively reduce interactions,compress time(30%~40%) and save expenditure(7%~20%).更多还原