A genetic algorithm based stochastic programming model for air quality management

Article type: Research Article

Authors: Ma, Xiao-ming | Zhang, Fan

Affiliations: Center for Environmental Sciences,Peking University,Beijing 100871,China

Abstract: 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.

Keywords: stochastic model, genetic algorithms, air quality management, optimization

Journal: Journal of Environmental Sciences, vol. 14, no. 3, pp. 367-374, 2002