{"title":"塑料管理供应链设计的优化方法","authors":"Shuheng Wang, Christos T. Maravelias","doi":"10.1002/aic.18464","DOIUrl":null,"url":null,"abstract":"<p>This article introduces three mixed integer programming (MIP) models to address a network design problem for mixed plastic waste (MPW) supply chains. By tracking waste compositions throughout the supply chain, the models optimize the technologies needed to process MPW. The three models adopt different approaches to preserve composition information in the supply chain. We also remark on how to improve solution times with additional constraints, and how the models can be easily modified to handle larger-scale problems. The proposed models provide an approach for examining emerging MPW recycling technologies that may be more sensitive to input composition, as well as determining the extent to which advanced sorting is useful.</p>","PeriodicalId":120,"journal":{"name":"AIChE Journal","volume":null,"pages":null},"PeriodicalIF":3.5000,"publicationDate":"2024-05-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aic.18464","citationCount":"0","resultStr":"{\"title\":\"Optimization methods for plastics management supply chain design\",\"authors\":\"Shuheng Wang, Christos T. Maravelias\",\"doi\":\"10.1002/aic.18464\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p>This article introduces three mixed integer programming (MIP) models to address a network design problem for mixed plastic waste (MPW) supply chains. By tracking waste compositions throughout the supply chain, the models optimize the technologies needed to process MPW. The three models adopt different approaches to preserve composition information in the supply chain. We also remark on how to improve solution times with additional constraints, and how the models can be easily modified to handle larger-scale problems. The proposed models provide an approach for examining emerging MPW recycling technologies that may be more sensitive to input composition, as well as determining the extent to which advanced sorting is useful.</p>\",\"PeriodicalId\":120,\"journal\":{\"name\":\"AIChE Journal\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":3.5000,\"publicationDate\":\"2024-05-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://onlinelibrary.wiley.com/doi/epdf/10.1002/aic.18464\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"AIChE Journal\",\"FirstCategoryId\":\"5\",\"ListUrlMain\":\"https://onlinelibrary.wiley.com/doi/10.1002/aic.18464\",\"RegionNum\":3,\"RegionCategory\":\"工程技术\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q2\",\"JCRName\":\"ENGINEERING, CHEMICAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"AIChE Journal","FirstCategoryId":"5","ListUrlMain":"https://onlinelibrary.wiley.com/doi/10.1002/aic.18464","RegionNum":3,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"ENGINEERING, CHEMICAL","Score":null,"Total":0}
Optimization methods for plastics management supply chain design
This article introduces three mixed integer programming (MIP) models to address a network design problem for mixed plastic waste (MPW) supply chains. By tracking waste compositions throughout the supply chain, the models optimize the technologies needed to process MPW. The three models adopt different approaches to preserve composition information in the supply chain. We also remark on how to improve solution times with additional constraints, and how the models can be easily modified to handle larger-scale problems. The proposed models provide an approach for examining emerging MPW recycling technologies that may be more sensitive to input composition, as well as determining the extent to which advanced sorting is useful.
期刊介绍:
The AIChE Journal is the premier research monthly in chemical engineering and related fields. This peer-reviewed and broad-based journal reports on the most important and latest technological advances in core areas of chemical engineering as well as in other relevant engineering disciplines. To keep abreast with the progressive outlook of the profession, the Journal has been expanding the scope of its editorial contents to include such fast developing areas as biotechnology, electrochemical engineering, and environmental engineering.
The AIChE Journal is indeed the global communications vehicle for the world-renowned researchers to exchange top-notch research findings with one another. Subscribing to the AIChE Journal is like having immediate access to nine topical journals in the field.
Articles are categorized according to the following topical areas:
Biomolecular Engineering, Bioengineering, Biochemicals, Biofuels, and Food
Inorganic Materials: Synthesis and Processing
Particle Technology and Fluidization
Process Systems Engineering
Reaction Engineering, Kinetics and Catalysis
Separations: Materials, Devices and Processes
Soft Materials: Synthesis, Processing and Products
Thermodynamics and Molecular-Scale Phenomena
Transport Phenomena and Fluid Mechanics.