针对具有学习效应的平行机排序模型,讨论了两类问题。在这一模型中,工件的实际加工时间不仅与其所在排序中的位置有关并且与其本身的学习率有关,对于在同一台机器上加工的工件,工件随位置的靠后其实际的加工时间减少。第1类问题的目标函数是极小化提前与延误的加权和;第2类问题的目标函数是极小化提前与误工工件数的加权和。对这两类问题分别给出了多项式算法。
We consider two models of the parallel machine scheduling problem with learning effect, where the actual processing times of jobs not only depend on the job position in a sequence, but also depend on the job-dependent learning rate. For the jobs to be processed on the same machine, their actual processing time is gradually reduced along with the order of their positions. The objective of the first problem is to minimize the sum of earliness and tardiness penalties. The objective of the second problem is to minimize the weighted sum of earliness and number of tardy jobs. For the two problems, we present two polynomial time algorithms, respectively.