具有学习效应的两台机上最优混合流水作业算法

研究相同工件在两台机器（分别称为机器M₁和M₂）上的混合流水作业问题，每个给定工件有两个任务，分别称之为任务A和任务B，任务B只能在任务A完工后才能开始加工，每个工件有两种加工模式供选择：模式1是将两个任务都安排在机器M₂上加工；模式2是将任务A和B分别安排在机器M₁和M₂上加工.假设在加工工件时，机器具有学习效应，即工件的实际加工时间与工件的加工位置有关.目标函数是最小化最大完工时间.分别讨论了具有无缓冲区与无限缓冲区两种加工环境情况，两种情况下都得到了最优算法.

Optimal algorithms for hybrid flow shop schedule on two machines with learning effect

In this paper, optimal algorithms are proposed for hybrid flow shop schedule of identical jobs on two machines (named as M₁ and M₂) with learning effect. In our problem, each job has two tasks, named as task A and task B respectively, and two optional processing modes. The task B can start to be processed only if after task A has been finished. The first processing mode, named as mode 1, is to assign both task A and B to machine M₂. The second processing mode, named mode 2, is to assign task A and B to machine M₁ and M₂, respectively. It is assumed that each machine has learning effect when processing the job, in other words, the actual processing time of the job is related to the processing position of the job. Our objective is to minimize the makespan. Optimal algorithms are given for two systems with no buffer and infinite buffer respectively.