A Simulation-Optimization Model for Dynamic Cellular Manufacturing System in Uncertainty Condition

Dynamic Cellular Manufacturing System (DCMS) is a new manufacturing system and in recent years this system has been attented by most of the researchers. While many available models focus only on one of the simulation or optimization aspects, in this research, we designed a comprehensive simulation-optimization model; which Discrete-Event Simulation (DES) has been used for modeling production processes, and robust optimization is used for handling uncertainties. Take into consideration that the studied problem is an NP-hard, hence Genetic Algorithm (GA) and Imperialist Competitive Algorithm (ICA) are used in this step to evaluate the mathematical model. As a result, the combination models can dramatically improve the quality of optimal solutions and increase the efficiency of manufacturing systems. These approaches can be further steps to develop simulation-optimization models in DCMSs and pave the way for more extensive studies in this field.