{"title":"闭环供应链网络中计算机电子废弃物可持续管理的多目标优化方法","authors":"Jorge David Restrepo Diaz, Saman Hassanzadeh Amin","doi":"10.1016/j.jclepro.2025.145494","DOIUrl":null,"url":null,"abstract":"<div><div>This study explores the integration of reverse and forward supply chains in a Closed-Loop Supply Chain (CLSC) for electronic waste management, driven by business and government regulatory concerns. It highlights the economic benefits and efficient management of Electronic Waste (E-waste), particularly focusing on End-of-Life (EoL) products to tackle the global E-waste crisis. This research introduces a novel multi-objective mixed-integer linear programming model adapted for an E-waste CLSC network. This model incorporates hybrid manufacturing facilities and Triple Bottom Line (TBL) objectives to maximize profits and social innovations while minimizing gas emissions to reduce landfill waste. An application involving a computer manufacturing network in Ontario, Canada, utilizing Google Maps for distance calculations, illustrates the design and optimization impact of an electronic CLSC network. This study employs computational experiments and sensitivity analyses, using three solution methods, including weighted-sum, <em>ε</em>-constraint, and hybrid approaches within a multiperiod framework to validate the model's robustness. These methods help decision-makers integrate a TBL approach into the CLSC network which reflects economic, environmental, and social factors. By generating Pareto optimal solutions using these methods, decision-makers can evaluate different options through trade-off analysis. The findings show that the <em>ε</em>-constraint method offers a greater number of efficient solutions, enabling a better balance of objectives. Finally, this study concludes with managerial insights and recommendations based on the research outcomes. The findings provide insights into product and part flows, facilities utilization, and distribution across the network segments.</div></div>","PeriodicalId":349,"journal":{"name":"Journal of Cleaner Production","volume":"506 ","pages":"Article 145494"},"PeriodicalIF":10.0000,"publicationDate":"2025-04-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"A multi-objective optimization approach for sustainable management of computers E-waste in a closed-loop supply chain network\",\"authors\":\"Jorge David Restrepo Diaz, Saman Hassanzadeh Amin\",\"doi\":\"10.1016/j.jclepro.2025.145494\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>This study explores the integration of reverse and forward supply chains in a Closed-Loop Supply Chain (CLSC) for electronic waste management, driven by business and government regulatory concerns. It highlights the economic benefits and efficient management of Electronic Waste (E-waste), particularly focusing on End-of-Life (EoL) products to tackle the global E-waste crisis. This research introduces a novel multi-objective mixed-integer linear programming model adapted for an E-waste CLSC network. This model incorporates hybrid manufacturing facilities and Triple Bottom Line (TBL) objectives to maximize profits and social innovations while minimizing gas emissions to reduce landfill waste. An application involving a computer manufacturing network in Ontario, Canada, utilizing Google Maps for distance calculations, illustrates the design and optimization impact of an electronic CLSC network. This study employs computational experiments and sensitivity analyses, using three solution methods, including weighted-sum, <em>ε</em>-constraint, and hybrid approaches within a multiperiod framework to validate the model's robustness. These methods help decision-makers integrate a TBL approach into the CLSC network which reflects economic, environmental, and social factors. By generating Pareto optimal solutions using these methods, decision-makers can evaluate different options through trade-off analysis. The findings show that the <em>ε</em>-constraint method offers a greater number of efficient solutions, enabling a better balance of objectives. Finally, this study concludes with managerial insights and recommendations based on the research outcomes. The findings provide insights into product and part flows, facilities utilization, and distribution across the network segments.</div></div>\",\"PeriodicalId\":349,\"journal\":{\"name\":\"Journal of Cleaner Production\",\"volume\":\"506 \",\"pages\":\"Article 145494\"},\"PeriodicalIF\":10.0000,\"publicationDate\":\"2025-04-10\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Cleaner Production\",\"FirstCategoryId\":\"93\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0959652625008443\",\"RegionNum\":1,\"RegionCategory\":\"环境科学与生态学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ENGINEERING, ENVIRONMENTAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Cleaner Production","FirstCategoryId":"93","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0959652625008443","RegionNum":1,"RegionCategory":"环境科学与生态学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, ENVIRONMENTAL","Score":null,"Total":0}
A multi-objective optimization approach for sustainable management of computers E-waste in a closed-loop supply chain network
This study explores the integration of reverse and forward supply chains in a Closed-Loop Supply Chain (CLSC) for electronic waste management, driven by business and government regulatory concerns. It highlights the economic benefits and efficient management of Electronic Waste (E-waste), particularly focusing on End-of-Life (EoL) products to tackle the global E-waste crisis. This research introduces a novel multi-objective mixed-integer linear programming model adapted for an E-waste CLSC network. This model incorporates hybrid manufacturing facilities and Triple Bottom Line (TBL) objectives to maximize profits and social innovations while minimizing gas emissions to reduce landfill waste. An application involving a computer manufacturing network in Ontario, Canada, utilizing Google Maps for distance calculations, illustrates the design and optimization impact of an electronic CLSC network. This study employs computational experiments and sensitivity analyses, using three solution methods, including weighted-sum, ε-constraint, and hybrid approaches within a multiperiod framework to validate the model's robustness. These methods help decision-makers integrate a TBL approach into the CLSC network which reflects economic, environmental, and social factors. By generating Pareto optimal solutions using these methods, decision-makers can evaluate different options through trade-off analysis. The findings show that the ε-constraint method offers a greater number of efficient solutions, enabling a better balance of objectives. Finally, this study concludes with managerial insights and recommendations based on the research outcomes. The findings provide insights into product and part flows, facilities utilization, and distribution across the network segments.
期刊介绍:
The Journal of Cleaner Production is an international, transdisciplinary journal that addresses and discusses theoretical and practical Cleaner Production, Environmental, and Sustainability issues. It aims to help societies become more sustainable by focusing on the concept of 'Cleaner Production', which aims at preventing waste production and increasing efficiencies in energy, water, resources, and human capital use. The journal serves as a platform for corporations, governments, education institutions, regions, and societies to engage in discussions and research related to Cleaner Production, environmental, and sustainability practices.