A multi-objective identical parallel machine scheduling with setup and removal times with deteriorating and learning effects

This paper considers an identical parallel machine scheduling problem when there are position-based deteriorating jobs with setup and removal times that are affected by the position-based learning effect. The aim of the problem is to minimize the sum of the total tardiness and earliness, minimize the number of tardy jobs and minimize the mean completion times. As a result, the mathematical model is developed for the above-mentioned problem. Since this problem belongs to NP-hard classes, three heuristic methods, namely shortest processing time (SPT), earliest due date (EDD) and longest processing time (LPT), are developed. Furthermore, some numerical experiments are designed to compare the performance of these different methods.