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作 者:施志晖 王景斌 黄进 SHI Zhihui;WANG Jingbin;HUANG Jin(Jiangsu Suning Bank Co.Ltd.,Nanjing 210019,China;School of Engineering Management,Nanjing University,Nanjing 210093,China)
机构地区:[1]江苏苏宁银行股份有限公司,江苏南京210019 [2]南京大学工程管理学院,江苏南京210093
出 处:《工业加热》2023年第4期50-53,63,共5页Industrial Heating
摘 要:以多目标优化为核心的碳排放规划方法,求解过程中偏重局部探索,存在约束条件不明确、碳排放量居高不下的问题,由此,提出基于二元蚁群算法的高碳制造业碳排放多目标规划方法。深入分析高碳制造业碳排放特征,提取企业碳排放驱动因素。经济增长目标和碳减排目标,建立多目标碳排放规划模型。在碳排放、能量消耗、投入产出、科技投入以及产业扩张等方面,分别设置规划约束条件,基于二元蚁群搜索原理,设计多目标规划求解算法,并引入一系列环境评价指标,加强“全局探索”和“局部搜索”之间的平衡性,生成最优规划方案。实证分析结果表明:所提多目标规划方法应用后,使得高碳制造业碳排放量降低了12.35%,促进了高碳制造业的节能减排发展。The carbon emission planning method with multi-objective optimization as the core focuses on local exploration in the solution process,which has the problems of unclear constraints and high carbon emission.Therefore,a multi-objective planning method for carbon emission of high-carbon manufacturing industry based on binary ant colony algorithm is proposed.Deeply analyze the carbon emission characteristics of high-carbon manufacturing industry and extract the driving factors of enterprise carbon emission.Economic growth targets and carbon emission reduction targets,and establish a multi-objective carbon emission planning model.In terms of carbon emission,energy consumption,input-output,science and technology investment and industrial expansion,planning constraints are set respectively.Based on the binary ant colony search principle,a multi-objective programming algorithm is designed,and a series of environmental evaluation indicators are introduced to strengthen the balance between “global exploration” and “local search” and generate the optimal planning scheme.The empirical analysis results show that the application of the proposed multi-objective planning method reduces the carbon emission of high-carbon manufacturing industry by 12.35%,and promotes the development of energy conservation and emission reduction of high-carbon manufacturing industry.
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