An artificial immune system heuristic for two-stage multi-machine assembly scheduling problem to minimize total completion time

• The practical two-stage assembly flowshop scheduling problem is addressed with respect to minimizing total completion time.
• A new heuristic, called artificial immune system, is proposed in this paper.
• It is shown that the new proposed heuristic reduces the error of the best existing heuristic by 60% while having the same computational times.

We address the two-stage multi-machine assembly scheduling problem. The first stage consists of m independently working machines where each machine produces its own component. The second stage consists of two independent and identical assembly machines. The objective is to come up with a schedule that minimizes total or mean completion time for all jobs. The problem has been addressed in the scheduling literature and several heuristics have been proposed. In this paper, we propose a new heuristic called artificial immune system (AIS). We conduct experimental analysis for comparing the newly proposed heuristic AIS with the best known heuristic in the literature. Experimental results show that our proposed heuristic AIS performs better than the best known existing heuristic. More specifically, our new heuristic AIS reduces the error of the best known heuristic by 60% while the computational times of both AIS and the best known heuristic are almost the same.