Mehrdad Nouri Koupaei - Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran
Mohammad Mohammadi - Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran
Bahman Naderi - Department of Industrial Engineering, Faculty of Engineering, Kharazmi University, Tehran, Iran

In recent decades, flexible manufacturing systems have emerged as a response to market demands of high product diversity. Scheduling is one important phase in production planning in all manufacturing systems. Although scheduling in classical manufacturing systems, such as flow and job shops, are well studied. Rarely, any paper studies scheduling of the more recent flexible manufacturing system. This paper investigates scheduling in the flexible manufacturing systems where there are both machine and routing flexibilities. In the first step, two mathematical models in form of mixed integer linear programs are proposed for the problem. The first model is position-based and the second is sequence-based. The models can solve optimally small problems. In the second step, since the problem is NP-hard, we develop an efficient genetic algorithm for large scale problems, using the properties of the optimal schedule. Finally, we carry out computational experiments to demonstrate the effectiveness of our algorithm. The results show that the proposed algorithm has the ability to achieve the good solutions in reasonable computational time.

scheduling, flexible manufacturing systems, mathematical model, genetic algorithm