Simulation-based control strategy optimization by using genetic algorithms

The paper describes simulation-based analysis and improvement of a production control system through a case-study. Emulation, which can be considered as a new improved way of testing control algorithms, is applied for modeling the behavior of the production environment. Connecting control system and emulation results in a simulation test environment as the basis of the analysis. We present a genetic algorithm (GA) based optimization solution (coupled with the developed simulation test environment), which is capable of finding appropriate control strategies for an intra-plant logistics system. Several production situations are tested, where the influence of the control strategy calculated by the proposed GA-based solution is analyzed and compared to the strategy currently applied in the production system. By applying the optimized strategies, a reasonable improvement of the selected performance measures can be experienced