带有学习效应的多客户配送的供应链排序问题

The Supply Chain Scheduling with Learning Effect and Multi-customers Distribution

针对机器具有学习效应,且需要多客户配送的供应链排序模型。在这一模型中,机器上工件加工时学习效应会发生,工件的实际加工时间是与其位置相关的减函数。客户需要接纳与其对应的完工工件,每一批次的工件完工后需要配送,然而配送都会花费一些时间及费用。由于大量客户需要配送,为了尽量节约资源,减少车次数量及运输次数,所以运输车辆都要尽可能多的装载货物才开始运输。在针对一台运输车辆内装载有不超过两个客户的工件情况,研究的目标函数为极小化总流程时间和极小化最大延迟时间,并对这两个问题分别给出了相应的动态规划算法。

The paper studies supply chain scheduling problems with learning effect and multi-customers distribution. The actualcompletion time is a non-increasing function of its position. The jobs are distributed to the corresponding customers after this jobscompleted. Each batch of distribution will take some time and cost. In order to save resource costs, reduce the number of trips, sotransport vehicles have to carry the goods as much as possible before the beginning of transportation. In this paper, the number ofcustomers transported in the same vehicle is not more than two. The objective function is to minimize the total flow times and themaximum lateness. Furthermore, we also present the corresponding dynamic programming algorithm.