Simulation optimization using tabu search

Investigation of the performance and operation of complex systems in manufacturing or other environments, analytical models of these systems become very complicated. Because of the complex stochastic characteristic of the systems, simulation is used as a tool to analyze them. The trust of such simulation analysis usually is to determine the optimum combination of factors that effect the considered system performance. The purpose of this study is to use a tabu search algorithm in conjunction with a simulation model of a JIT system to find the optimum number of kanbans.