An Automatic Approach for Parameter Optimization of Material Flow Simulation Models based on Particle Swarm Optimization

Abstract- The analysis of production systems by the use of discrete, event-based simulation is widely used and accepted as decision support method. It aims either at the comparison of competitive designs or the identification of a “best possible” configuration of the simulation model. Here, combinatorial techniques of simulation and optimization methods support the user in finding optimal solutions, which typically result in long computation times and though often prohibit a practical application in today’s industry. This paper presents a fast converging procedure as a combination of a swarm heuristic, namely the particle swarm optimization, and the material flow simulation to close this gap. Faster convergence is realized by a specific extension of classic PSO implementations. First results show the applicability with a simulation reference model. Keywords-Design of Experiments; DES; meta-heuristics; particle swarm optimization; parameter optimization. I