Simulation optimization through direct search for multi-objective manufacturing systems

Simulation modelling has been one of the most widely used techniques for analysing complex manufacturing systems. In this paper, we propose a direct search algorithm expanded from the Hooke-Jeeves pattern search to systematically and efficiently locate satisfactory solutions for multi-objective simulation models. The user-specified goals can be precise and/or fuzzy. Heuristic rules stemming from the simulation result of resource statistics are incorporated into the Hooke-Jeeves pattern search. The proposed heuristic rules make the search procedure effective regardless of different initial points and various bounded ranges of decision variables. Experimental results show that the proposed approach is suitable for analysing complex manufacturing systems, in which multiple objectives and multiple decision variables are encountered.