A genetic algorithm based stochastic programming model for air quality management

作     者：MaXM ZhangF 

作者机构：CenterforEnvironmentalSciencesPekingUniversityBeijing100871China.E－mail：zhangfan@*** CenterforEnvironmentalSciencesPekingUniversityBeijing100871China.E－mail：zhangfan@water.pku.edu.c 

出 版 物：《Journal of Environmental Sciences》 (环境科学学报（英文版）)

年 卷 期：2002年第14卷第3期

页      面：367-374页

核心收录：

学科分类：07[理学] 070602[理学-大气物理学与大气环境] 0706[理学-大气科学] 

主　　题：stochastic model genetic algorithms air quality management optimization 

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.