Solving Open Shop Scheduling Problem with Two Criteria Using A New Optimization Method

This paper addresses the open shop scheduling problem. this problem, due to its complexity, is ranked in the class of NPhard problems. In this case, traditional approaches cannot reach to an optimal solution in a reasonable time. So heuristic algorithms such as simulated Annealing (SA), tabu search (TS) genetic algorithm, (GA), ant colony optimization (ACO) used to solve optimization problems such as Open Shop Scheduling. In this paper, a hybrid optimization algorithm based on management of an organization (MOA) is proposed to solve Open Shop Scheduling more efficiently and accurately. Most literature referring to OSSP focuses on the optimization of one single objective. This paper considers an open shop scheduling problem that minimizes bi-objectives, namely makespan and total tardiness. The proposed method was then compared whit the results of the LINGO software, GA and PSO. The results of this comparison show that MOA can achieve results in a faster time.