{"title":"A Distributionally Robust Fuzzy Optimization Approach for Resilient Manufacturing Supply Chain Network Design: An RCEP Perspective","authors":"Xinxuan Cheng;Luqi Wang;Jiachen Wang","doi":"10.1109/TFUZZ.2023.3324207","DOIUrl":null,"url":null,"abstract":"Recent changes in trade barriers and increasing uncertainties in trade policies have forced companies to rethink their optimal supply chain settings. This article studies the impact of the regional comprehensive economic partnership (RCEP) agreement, particularly the cumulative rules of origin, on the resilient manufacturing supply chain network design problem with demand uncertainty. Three resilience strategies, namely, multiple sourcing, capacity redundancy, and technology innovation, are employed to improve supply chain resilience. Using type-2 fuzzy theory, we develop a distributionally robust fuzzy optimization (DRFO) model to address the proposed problem. In this model, the demand is represented as a parametric interval-valued fuzzy variable and its associated uncertainty distribution set. In terms of the model's tractability, we analyze the computational issues of the credibility constraint and reformulate the DRFO model into a computationally tractable mixed-integer linear program. Finally, we apply the proposed model to a real-life automotive supply chain case and demonstrate its superiority in providing uncertainty-immunized solutions. Our analysis reveals that the RCEP agreement may deepen the manufacturing supply chain networks in Asia–Pacific and promote their integration and localization. Also, we find that using any resilience strategy or a mixture of them can increase supply chain's resilient performance while decreasing costs against disruptions.","PeriodicalId":13212,"journal":{"name":"IEEE Transactions on Fuzzy Systems","volume":"32 3","pages":"1359-1369"},"PeriodicalIF":11.9000,"publicationDate":"2023-10-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Transactions on Fuzzy Systems","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10283919/","RegionNum":1,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Recent changes in trade barriers and increasing uncertainties in trade policies have forced companies to rethink their optimal supply chain settings. This article studies the impact of the regional comprehensive economic partnership (RCEP) agreement, particularly the cumulative rules of origin, on the resilient manufacturing supply chain network design problem with demand uncertainty. Three resilience strategies, namely, multiple sourcing, capacity redundancy, and technology innovation, are employed to improve supply chain resilience. Using type-2 fuzzy theory, we develop a distributionally robust fuzzy optimization (DRFO) model to address the proposed problem. In this model, the demand is represented as a parametric interval-valued fuzzy variable and its associated uncertainty distribution set. In terms of the model's tractability, we analyze the computational issues of the credibility constraint and reformulate the DRFO model into a computationally tractable mixed-integer linear program. Finally, we apply the proposed model to a real-life automotive supply chain case and demonstrate its superiority in providing uncertainty-immunized solutions. Our analysis reveals that the RCEP agreement may deepen the manufacturing supply chain networks in Asia–Pacific and promote their integration and localization. Also, we find that using any resilience strategy or a mixture of them can increase supply chain's resilient performance while decreasing costs against disruptions.
期刊介绍:
The IEEE Transactions on Fuzzy Systems is a scholarly journal that focuses on the theory, design, and application of fuzzy systems. It aims to publish high-quality technical papers that contribute significant technical knowledge and exploratory developments in the field of fuzzy systems. The journal particularly emphasizes engineering systems and scientific applications. In addition to research articles, the Transactions also includes a letters section featuring current information, comments, and rebuttals related to published papers.