Optimizing a Two-stage Supply Chain System with Coordinated Scheduling

In this paper, the problem of scheduling in a two-stage supply chain system is investigated with considering coordinated scheduling of different stages. The objective is to find the similar sequences of processing tasks in two steps with two aims of minimizing the total preparation time as well as the maximum preparation time of each stage. To do so, the problem has been solved by non-dominant sorting genetic algorithm (NSGA-II) and using a variety of multi-objective techniques. The proposed meta-heuristic algorithm is applied for the first time in this problem. The results show that the proposed algorithm is able to find Pareto optimal solutions with a high efficiency.