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作 者:姜芳 郭健全[2] JIANG Fang;GUO Jianquan(Business School,University of Shanghai for Science and Technology,Shanghai 200093,China;Shanghai-Hamburg College,University of Shanghai for Science and Technology,Shanghai 200093,China)
机构地区:[1]上海理工大学,管理学院,上海200093 [2]上海理工大学,上海-汉堡国际工程学院,上海200093
出 处:《上海理工大学学报》2018年第3期274-281,共8页Journal of University of Shanghai For Science and Technology
基 金:国家自然科学基金资助项目(71071093,71471110); 陕西省社会科学基金资助项目(2015D060)
摘 要:针对塑料制品的回收与再利用问题,构建了以最小网络总成本、最低碳交易成本及最小环境影响程度为目标函数的碳交易环境下多目标多周期多阶段政企结合逆向物流网络动态联建模型。并以上海市废旧塑料制品回收为例,采用遗传算法和粒子群算法验证了模型的有效性。结果表明,该模型有助于减少对环境的负面影响、降低系统总成本、优化各阶段的资源输入,为政企结合逆向物流网络联建提供了借鉴。In view of the recycling and reutilization of plastic products, an integrated multi-objective multi-period multi-stage government-enterprise dynamic joint model for the recycling of used plastic products was constructed under the environment of carbon trading and its optimal operation was discussed. The minimums of network cost, carbon emission cost and environmental impact were taken as the objective functions. Then the feasibility of the optimization model was validated by using the geneti algorithm and particle swarm optimization algorithm, taking the recyding of used plastic products in Shanghai as a calculation example. The results reveal that the negative effect of operation of the system on the surroundings is minimized, the total cost of the system is decreased and the input resources are optimized because of the multi-period arrangement. The study could provide a reference for the construction of government-enterprise reverse logistics network design.
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