Genetic algorithm with initial sequence for parallel machines scheduling with sequence dependent setup times based on earliness- tardiness

The first objective of this study is to update a capacity constraint to the mixed integer programming model of the unrelated parallel machines scheduling problem. Then, a new proposed algorithm is developed based on the combination between the genetic algorithm with the so-called ISETP heuristics (Initial Sequence based on Earliness-Tardiness criterion on Parallel machine). The new Genetic Algorithm with Initial Sequence based on Earliness-Tardiness criterion on Parallel machine (GAISETP) generates job sequences and allocates them to the machines subject to capacity constraint. A case of automobile component manufacturing company is investigated to test the performance of the proposed method for both small-sized and large-sized problems. The obtained results are very promising both in terms of makespan and earliness-tardiness.