• 关键词：VOCs  联防联控  多目标进化算法  减排方案

• 基金项目：国家自然科学基金项目（No.71874134）

• 陆秋琴
• 西安建筑科技大学管理学院, 西安 710055

• 何舒
• 西安建筑科技大学管理学院, 西安 710055

• 黄光球
• 西安建筑科技大学管理学院, 西安 710055

• 摘要：VOCs区域性联防联控治理是当前彻底治理VOCs污染的有效手段，为了实现VOCs区域性联防联控治理，建立了以减排总量最大、减排成本最低、VOCs减排限产产生的经济影响最小为目标的多目标最优减排模型，提出了基于自适应变异率的分解多目标进化算法（Decomposition Multi-objective Evolutionary Algorithm based on Adaptive Mutation Rate，简称MOEA/DAMA）.选取关中某城市群为研究对象，将VOCs的排放数据代入到最优减排模型中，运用MOEA/DAMA算法对其求解.根据最终的优化结果与MOEA/D初始算法和NSGA-Ⅱ优化算法的优化结果进行对比，结果表明MOEA/DAMA相较于NAGA-Ⅱ和MOEA/D的Pareto解的分布性更广、解的收敛性更高.在对Pareto解的分析上融入决策者的根据实际情况的权衡，计算出更合理的VOCs最优减排方案，为长效科学治理VOCs污染提供借鉴.

• Abstract：The regional joint prevention and control of VOCs has been proposed as effective strategies to thoroughly control VOCs pollution. In order to realize the regional joint prevention and control of VOCs, a multi-objective optimal emission reduction model with the goal of maximizing total emission reduction, minimizing cost of emission reduction and minimizing economic impact caused by production restriction of VOCs is established. A decomposition multi-objective evolutionary algorithm based on adaptive mutation rate, or MOEA/DAMA in short,is proposed to solve the model. Taking a city group in Guanzhong as the research object, the VOCs emission data is simulated by the multi-objective optimal emission reduction model, and the MOEA/DAMA algorithm is used to solve the model. The results show that the Pareto solutions of MOEA/DAMA are more widely distributed and the convergence of solutions is higher than that of NAGA-Ⅱ and MOEA-Ⅱ. The decision-maker's trade-off based on the actual situation is integrated into the analysis of the Pareto solutions. Then a more reasonable optimal VOCs emission reduction scheme is calculated, which provides a reference for the long-term scientific control of VOCs pollution.

• Key words：VOCs  joint prevention and control  multi-objective evolutionary algorithm  emission reduction scheme

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