{"title":"在不确定情况下设计新的稳健固体废物回收网络:循环经济转型案例研究","authors":"Yilin Wang , Yankui Liu , Huili Pei","doi":"10.1016/j.seps.2024.102066","DOIUrl":null,"url":null,"abstract":"<div><p>Solid waste generation continuously puts tremendous pressure on human health, socio-economic and environmental protection, and many regions are transitioning to the circular economy using waste recycling to advance sustainable development. A more practical and integrated solid waste recycling network (SWRN) design is essential for solid waste recycling management, which can be complex and uncertain. Therefore, this paper focuses on the design of a robust SWRN that aims to optimize the construction of sorting centers (SCs) while robustly operating with waste recycling allocation. This approach often involves two main challenges related to the uncertainty of unknown distribution information and the bi-level structure of decision making. To address these challenges, we first present two pairs of uncertainty sets to capture the separation rate and transportation cost in the case of free distribution information. Then, we develop a bi-level framework that integrates SC construction locations and waste operation allocation. For this purpose, a globalized robust optimization bi-level model is developed and reformulated into a mixed integer linear programming. We apply this methodology to the case of Baoding, China to demonstrate its validity. The main numerical achievements show that: (1) the proposed model can hedge the uncertainty in the separation rate and transportation cost with a small price of robustness and provide a robust recovery scheme; (2) the average operating cost of our model for a single period is approximately 19.4% lower than that of the classical robust model; and (3) by adjusting several parameters based on the preferences of waste recycling managers, a balance between operating costs and robustness can be achieved. Finally, some managerial insights are obtained to assist waste recycling managers in solid waste recycling management transition to the circular economy.</p></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"96 ","pages":"Article 102066"},"PeriodicalIF":6.2000,"publicationDate":"2024-09-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Designing a new robust solid waste recycling network under uncertainty: A case study about circular economy transition\",\"authors\":\"Yilin Wang , Yankui Liu , Huili Pei\",\"doi\":\"10.1016/j.seps.2024.102066\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Solid waste generation continuously puts tremendous pressure on human health, socio-economic and environmental protection, and many regions are transitioning to the circular economy using waste recycling to advance sustainable development. A more practical and integrated solid waste recycling network (SWRN) design is essential for solid waste recycling management, which can be complex and uncertain. Therefore, this paper focuses on the design of a robust SWRN that aims to optimize the construction of sorting centers (SCs) while robustly operating with waste recycling allocation. This approach often involves two main challenges related to the uncertainty of unknown distribution information and the bi-level structure of decision making. To address these challenges, we first present two pairs of uncertainty sets to capture the separation rate and transportation cost in the case of free distribution information. Then, we develop a bi-level framework that integrates SC construction locations and waste operation allocation. For this purpose, a globalized robust optimization bi-level model is developed and reformulated into a mixed integer linear programming. We apply this methodology to the case of Baoding, China to demonstrate its validity. The main numerical achievements show that: (1) the proposed model can hedge the uncertainty in the separation rate and transportation cost with a small price of robustness and provide a robust recovery scheme; (2) the average operating cost of our model for a single period is approximately 19.4% lower than that of the classical robust model; and (3) by adjusting several parameters based on the preferences of waste recycling managers, a balance between operating costs and robustness can be achieved. Finally, some managerial insights are obtained to assist waste recycling managers in solid waste recycling management transition to the circular economy.</p></div>\",\"PeriodicalId\":22033,\"journal\":{\"name\":\"Socio-economic Planning Sciences\",\"volume\":\"96 \",\"pages\":\"Article 102066\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-09-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Socio-economic Planning Sciences\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0038012124002659\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038012124002659","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
Designing a new robust solid waste recycling network under uncertainty: A case study about circular economy transition
Solid waste generation continuously puts tremendous pressure on human health, socio-economic and environmental protection, and many regions are transitioning to the circular economy using waste recycling to advance sustainable development. A more practical and integrated solid waste recycling network (SWRN) design is essential for solid waste recycling management, which can be complex and uncertain. Therefore, this paper focuses on the design of a robust SWRN that aims to optimize the construction of sorting centers (SCs) while robustly operating with waste recycling allocation. This approach often involves two main challenges related to the uncertainty of unknown distribution information and the bi-level structure of decision making. To address these challenges, we first present two pairs of uncertainty sets to capture the separation rate and transportation cost in the case of free distribution information. Then, we develop a bi-level framework that integrates SC construction locations and waste operation allocation. For this purpose, a globalized robust optimization bi-level model is developed and reformulated into a mixed integer linear programming. We apply this methodology to the case of Baoding, China to demonstrate its validity. The main numerical achievements show that: (1) the proposed model can hedge the uncertainty in the separation rate and transportation cost with a small price of robustness and provide a robust recovery scheme; (2) the average operating cost of our model for a single period is approximately 19.4% lower than that of the classical robust model; and (3) by adjusting several parameters based on the preferences of waste recycling managers, a balance between operating costs and robustness can be achieved. Finally, some managerial insights are obtained to assist waste recycling managers in solid waste recycling management transition to the circular economy.
期刊介绍:
Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry.
Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution.
Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.