Multi-attribute Decision-Based Multi-objective Optimization for Regional Atmospheric Compound Pollution Control

Atmospheric compound pollution is the primary atmospheric environmental problem in China. Reducing the emissions of primary and secondary pollution precursors is an effective method to control atmospheric compound pollution. In this study, we propose a new multi-objective optimal control model of regional atmospheric compound pollution. Multi-objective evolution algorithms and multi-attribute decision methods based on preference are used to formulate the optimal strategies for this model. As a prerequisite to ensure that air quality is up to standard, our method, which is different from the most commonly used single-objective methods, can achieve a balance between cost and development. We believe that this method will be helpful in making scientific strategies to control regional atmospheric compound pollution.