Hybrid approach in a production line for multi-objective simulation optimization

To adapt changing market conditions, firms must make quick decisions and response the changes as fast as possible. Simulation is a powerful tool to analyze the effects of changes in industrial or service systems. But simulation isn't adequate to optimize the systems and additional methods are needed to integrate simulation and optimization. A multi-objective optimization of a production system is considered and management aims to decide the optimal combination of workers in certain workstations of the considered system. In this study meta-modelling is used to represent the system by means of the simulation run results and grey relational analysis is used to combine two separate responses into one value. The optimal combination of the workers in the considered workstations is decided subject to certain constraints at the end of the study.