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作 者:徐帆 金玉兰[1] XU Fan;JIN Yu-lan(School of Management,Shanghai University of Science and Technology,Shanghai 201620,China)
出 处:《物流工程与管理》2024年第11期83-90,共8页Logistics Engineering and Management
摘 要:为解决半导体设备首件供应商选择与订单分配(SSOA)过程中忽视装配关系的问题,提出了一种融入零部件装配数量和装配顺序关系的多物料SSOA联合求解模型。该模型以最大化供应提前率和组件需求满足率,最小化预算消耗率和装配滞后率为目标,采用改进遗传算法的矩阵编码、自交叉与点变异等方式提升求解效率。通过仿真实验确定性能最佳的初始种群大小和迭代次数,并与TOPSIS算法进行对比测试。算例结果表明,该模型能够在多物料半导体设备的SSOA问题中为主制造商提供有效的决策参考。In order to solve the problem of neglecting assembly relationships in the process of supplier selection and order allocation(SSOA) for the first article of semiconductor equipment,a multi-mterial SSOA optimization model was proposed,which incorporates component assembly quantity and sequence relationships.With the goal of maximizing supply lead rate and component demand satisfaction rate while minimizing budget consumption rate and assembly delay rate,the matrix encoding,self-crossover,and point variation of an improved genetic algorithm were used for enhancing the solution efficiency.The size of initial population with optimal performance,and the number of iterations are determined through simulation experiment,and a comparison test with TOPSIS algorithm is conducted.The results show that this model can provide effective decision-making support for main manufacturers dealing with multi-material semiconductor equipment SSOA problems.
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