Design And Optimization For Stochastic Many-objective Coal Production Model

The development of the carbon industry plays an important role in China's industrial development.The traditional coal energy structure brings some problems,such as,serious environmental pollution,low energy utilization,causing some certain degree of damage to the ecological environment.With the deepening of green development awareness,the efficient and environmentally friendly coal resource development way is imperative.It can not only meet China's own sustainable development requirements,but also slow down the climate and environmental changes.To this end,this paper considers various factors and proposes an uncertain many-objective stochastic coal model and designs the many-objective algorithm for the model.Firstly,the coal mining area system is intricate.First of all,in order to better achieve sustainable development,considering from the aspects of economy,environment,energy,security,at the same time,the uncertain variables,such as coal price and emissions are analyzed.The economic benefits,energy benefits,environmental benefits,coal gangue benefits and safety benefit of five objective functions are proposed for many-objective expectation model.Since the random constrained variables in the expected value model do not have a clear range,a confidence interval is set to constrain the uncertain variables,and a many-objective coal opportunity constrained model is proposed.Secondly,the many-objective coal expectation model mentioned in this article contains five-objective optimization at the same time.Because of the large number of objectives included,a many-object intelligent algorithm is used for the model.For the classic NSGA-III algorithm,in order to further improve the diversity of the algorithm,the range of alternative solutions is increased by using different stochastic distribution strategies.The less effective solutions are replaced during the solution of the model,which can be better get the solution result of the model.In addition,in the experimental part,a variety of many-objective algorithms are for the model and the proposed algorithm performance is analyzed.Finally,for the solution of coal many-objective opportunity constraint model,it is also the solution of high-dimensional many-objective model.Firstly,the stochastic simulation method is used to describe the uncertain variables,and the mixed strategy NSGA-III algorithm is designed for the model.The adaptive strategy is used to delete redundant reference points.The PBI distance strategy is used to improve the convergence and distribution of the solution set.The comparison experiments of various algorithms show that the proposed algorithm has better performance in solving the model.