Optimization of Air Pollutant Monitoring Stations Based on Genetic Algorithm

Reasonable sitting an air quality monitoring stations (AQMS) network is an important task for environmental protection department. However, involving many factors, optimizing air quality monitoring sites has been proven to be in the class of nondeterministic polynomial (NP)-hard problem. The powerful search capability of the genetic algorithm (GA) is a key factor in improving the performance of selecting optimal monitoring sites. A mathematical programming model is proposed, which the GA is used in order to optimize AQMS. The environmental, social, and economic objectives are considered in the optimization model. Modelling results suggest that the proposed approach outperforms the method of random site of AQMS.