Using system dynamics for simulation and optimization of one coal industry system under fuzzy environment

In this paper, we have developed a model that integrates system dynamics with fuzzy multiple objective programming (SD-FMOP). This model can be used to study the complex interactions in a industry system. In the process of confirming sensitive parameters and fuzzy variables of the SD model, we made use of fuzzy multi-objective programming to help yield the solution. We adopted the chance-constraint programming model to convert the fuzzy variables into precise values. We use genetic algorithm to solve FMOP model, and obtain the Pareto solution through the programming models. It is evident that FMOP is effective in optimizing the given system to obtain the decision objectives of the SD model. The results recorded from the SD model are in our option, reasonable and credible. These results may help governments to establish more effective policy related to the coal industry development.

► We develope a model that integrates system dynamics with fuzzy multiple objective programming.
► Fuzzy multi-objective programming can be used to optimize sensitive parameters of SD model.
► We adopt the chance-constraint programming model to convert the fuzzy variables into precise values.
► Effective policy related to the coal industry development can be established based on simulation.