Simulation-based optimization of production flows in a job shop department

This thesis addresses the problem of a simultaneous scheduling of machines and transporters in a job shop manufacturing system with the objective of minimizing the total tardiness. The problem analyzed is related to a real case: Loro Piana finishing department. The problem is formulated as a mixed integer linear programming model. The mathematical model of the problem is a complex NP-hard optimization problem. A first model is presented that tries to solve the Job Shop scheduling problem together with the scheduling of the transports. Since the model described can’t be solved in an efficient way using state-of-the-art methods, principally because of the large number of binary variables used to formulate the constraints of the problem. An alternative solution approach to reduce the complexity of the model is proposed and the original model is decomposed into two subproblems to make the problem easier to solve. The first one is the classical job shop scheduling problem while the second one is a pickup and delivery problem. Despite the decomposition of the original model into two subproblems it still remains quite complex to efficiently solve the optimization problem of the finishing department, due to the amount of jobs processed every day by the system and the high number of machines on which every job has to be worked. Further studies would be necessary to propose an appropriate method to solve this complex problem in an efficient way. For the purpose of this study, a preliminary solution obtained using a commercial optimization software compatible with Arena Simulation Software, called OptQuest, is proposed, in which the objective function also comprehend the minimization of the resources allocated to transports considering different cost’s scenarios.