作　　者： ; ; ;

机构地区： 曲阜师范大学管理学院

出　　处： 《系统科学与数学》 2013年第7期799-806,共8页

摘　　要： 研究了机器具有学习效应的供应链排序问题.有多个客户分布在不同位置,每个客户都有一定数量的工件需要在一台机器上进行加工.每个客户的工件在机器上加工时具有学习效应,即后面加工的工件实际加工时间是逐渐缩短的.工件生产完后需要运输到相应的客户处,每一批配送需要花费一定的时间和费用.这里研究了供应链排序理论中主要的四个目标函数,分析了这些问题的复杂性,对于一些情况给出了它们的最优算法. We consider supply chain scheduling with learning effects. Multiple customers located at different sites have a lot of jobs to be processed on a single machine. There are learning effects when the jobs are processed on the machine, which means the actural processing time of the job is decreased when there are some jobs processed before this job. Processed jobs are delivered in batches to their respective customers, each shipment incurs a delivery cost and takes a fixed amount of time. We study four main objective functions in supply chain scheduling theory, analyse the problem complexity and provide optimal algorithms for multiple cases.

关 键 词： 供应链排序 学习效应 分批配送 动态规划

领　　域： [理学] [理学]