A genetic algorithm based stochastic programming model for air quality management

查看全文 作　　者：[1]MaXM;[2]ZhangF

机构地区：[1]CenterforEnvironmentalSciences,PekingUniversity,Beijing100871,China.E-mail:zhangfan@water.pku.edu.cn;[2]CenterforEnvironmentalSciences,PekingUniversity,Beijing100871,China.E-mail:zhangfan@water.pku.edu.c

出　　处：《Journal of Environmental Sciences》索引2002年第14卷第3期,共8页

摘　　要：This paper presents a model that can aid planners in defining the total allowable pollutant discharge in the planning region, accounting for the dynamic and stochastic character of meteorological conditions. This is accomplished by integrating Monte Carlo simulation and using genetic algorithm to solve the model. The model is demonstrated by using a realistic air urban scale SO 2 control problem in the Yuxi City of China. To evaluate effectiveness of the model, results of the approach are shown to compare with those of the linear deterministic procedures. This paper also provides a valuable insight into how air quality targets should be made when the air pollutant will not threat the residents’ health. Finally, a discussion of the areas for further research are briefly delineated. 关键词：随机模式遗传算法空气质量管理最佳化

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A genetic algorithm based stochastic programming model for air quality management

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