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.

[1]  Mitsuo Gen,et al.  Genetic algorithms and engineering optimization , 1999 .

[2]  Parag C. Pendharkar A fuzzy linear programming model for production planning in coal mines , 1997, Comput. Oper. Res..

[3]  Walter C. Labys,et al.  Market transition and regional adjustments in the Polish coal industry , 2002 .

[4]  Ludovic Stephan,et al.  Simulations of accidental coal immersion. , 2007, Marine pollution bulletin.

[5]  H. Christopher Frey,et al.  Coal blending optimization under uncertainty , 1995 .

[6]  Gerry Riley,et al.  The effect of mineral additions on coal ash deposition , 2007 .

[7]  Moosung Jae,et al.  A quantitative assessment of LCOs for operations using system dynamics , 2005, Reliab. Eng. Syst. Saf..

[8]  Jing-Xuan Zhou,et al.  Dynamic Modeling of a Man–Land System in Response to Environmental Catastrophe , 2004 .

[9]  G. Slowinski,et al.  Some technical issues of zero-emission coal technology , 2006 .

[10]  J. Forrester,et al.  The system dynamics national model: Understanding socio-economic behavior and policy alternatives , 1976 .

[11]  M. Chakraborty,et al.  Multicriteria decision making for optimal blending for beneficiation of coal: a fuzzy programming approach , 2005 .

[12]  Thomas L. Robl,et al.  Adsorption of Hg and NOX on coal by-products , 2005 .

[13]  Yi-Ming Wei,et al.  A system dynamics based model for coal investment , 2007 .

[14]  Wojciech Suwala,et al.  Modelling adaptation of the coal industry to sustainability conditions , 2008 .

[15]  Shin-Cheng Yeh,et al.  Simulation of soil erosion and nutrient impact using an integrated system dynamics model in a watershed in Taiwan , 2006, Environ. Model. Softw..

[16]  Ching-Lai Hwang,et al.  Fuzzy Multiple Attribute Decision Making - Methods and Applications , 1992, Lecture Notes in Economics and Mathematical Systems.

[17]  Jun Li,et al.  A class of multiobjective linear programming model with fuzzy random coefficients , 2006, Math. Comput. Model..

[18]  Guanghui Zhao,et al.  CMEOC—An expert system in the coal mining industry , 1999 .

[19]  Noriaki Ebara R&D of coal utilization technology in Japan , 2000 .

[20]  S. Chehreh Chelgani,et al.  Prediction of microbial desulfurization of coal using artificial neural networks , 2007 .