Production optimal scheduling technology based on simulation

Current scheduling approach cannot construct a precise scheduling model and obtain satisfactory scheduling result at the same time. To deal with this problem, an optimal scheduling approach based on simulation optimization methodology was presented which was composed of three basic modules: experiment design module, Genetic Algorithm (GA) module and simulation model. Firstly, a combinatorial plan of parameter values for GA was designed by the orthogonal test. Then, a set of optimal scheduling rule sequence was obtained by repeated iteration of each parameter value and simulation model, therefore the corresponding performance index value of the production system was also obtained. The performance index value was returned to experiment design module and next set of plan was selected to conduct repeated iteration. The best combinatorial parameter value for GA and the optimal scheduling result were defined after completing all experiments and comparing test results. Validity and feasibility of this approach were proved by a case study in the workshop of a research institution.