A Knowledge-Oriented Heuristic Algorithm for Solving Simulation Optimization Problems

Simulation optimization is a hot and new topic in the fields of system simulation,operational research and so on.In view of the hardness of the simulation optimization of discrete event dynamical systems,the paper presents a novel knowledge-oriented heuristic algorithm.This method integrates the knowledge model with the heuristic searching model.The heuristic searching model plays an essential role and the knowledge model plays an important assistant role in this technique.Through appropriate combination and indispensable supplement,these two models can improve the optimization effectiveness of the proposed approach.Numerical simulation based on work shop production problem demonstrates the feasibility and effectiveness of the proposed approach.The experimental results have shown that the proposed approach has good performance with respect to the quality of solution and the speed of computation.The research results of this paper suggest that integrating the knowledge model with the heuristic searching model is an efficacious approach for the complex simulation optimization problems.