基于多属性决策的区域大气复合污染多目标优化控制方法研究

大气复合污染是我国目前面临的主要大气环境问题。科学减排对大气复合污染形成起主要作用的一次污染物和二次污染的前体物,是治理大气复合污染的有效手段。本文提出了一种新的区域大气复合污染多目标优化模型,并结合多目标进化算法和基于决策者偏好的多属性决策技术,寻找治理大气污染的最优控制策略。与传统的单目标优化控制技术相比,本文提出的方法在保证环境达标的前提下,同时兼顾治理成本和行业可持续性发展这两种在一定程度上互斥的目标,并融入了决策者从当地实际情况出发对目标重要性的权衡,更加符合管理实践的需求,可为科学治理区域大气复合污染提供借鉴。

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.