Properties for due window assignment scheduling on a two-machine no-wait proportionate flow shop with learning effects and resource allocation
Yu Sun, Dan‐Yang Lv, Xue Huang
Abstract
In actual production and processing, factories often have multiple production lines, then the two-machine no-wait proportionate flow shop scheduling problem with learning effects and resource allocation is investigated in this paper, where the processing time of the jobs are the position-dependent learning effects, and the corresponding amount of resources are allocated. Under two classical common as well as slack due window assignments, the goal is to find the optimal job processing order to minimize the sum of total weighted earliness, tardiness, the number of early jobs and tardy jobs, window start time, window size, and total resource cost. By the optimal solution properties, we show that both due window assignments can be transformed into assignment problems. We also illustrate the exact solution procedure by giving an example of a common due window assignment.