{"title":"Equilibrium Optimizer for Supply Chain Design Under Demand Uncertainty","authors":"Xiaofang Li;Pei Hu;Jiulong Zhu","doi":"10.1109/ACCESS.2025.3548146","DOIUrl":null,"url":null,"abstract":"Supply chain design (SCD) is a complex optimization challenge that involves coordinating various elements of a supply chain to ensure efficient production, distribution, and fulfillment of customer demands. This paper proposes an improved equilibrium optimizer (IEO) algorithm to develop a supply chain network. The first novelty lies in considering the uncertainty of customer demands, the upper and lower product limits of manufacturers, and product discounts to minimize the total economic cost. The second novelty concerns the improvements to the EO algorithm in the equilibrium pool, control parameters, and position correction. Position correction ensures that solutions meet the various constraints of SCD, and improves the feasibility of the algorithm. For small-, medium-, and large-scale test cases, the proposed algorithm has been observed to outperform the original EO algorithm and four well-known algorithms, the imperialist competitive algorithm (ICA), a hybrid algorithm of grey wolf optimizer and particle swarm optimization (GWOPSO), the whale optimization algorithm (WOA), and the teaching-learning based optimization algorithm (TLBO), in terms of optimal solutions and operational efficiency. IEO demonstrates outstanding performance in solving SCD problems.","PeriodicalId":13079,"journal":{"name":"IEEE Access","volume":"13 ","pages":"42285-42295"},"PeriodicalIF":3.4000,"publicationDate":"2025-03-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=10910140","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Access","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/10910140/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q2","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
引用次数: 0
Abstract
Supply chain design (SCD) is a complex optimization challenge that involves coordinating various elements of a supply chain to ensure efficient production, distribution, and fulfillment of customer demands. This paper proposes an improved equilibrium optimizer (IEO) algorithm to develop a supply chain network. The first novelty lies in considering the uncertainty of customer demands, the upper and lower product limits of manufacturers, and product discounts to minimize the total economic cost. The second novelty concerns the improvements to the EO algorithm in the equilibrium pool, control parameters, and position correction. Position correction ensures that solutions meet the various constraints of SCD, and improves the feasibility of the algorithm. For small-, medium-, and large-scale test cases, the proposed algorithm has been observed to outperform the original EO algorithm and four well-known algorithms, the imperialist competitive algorithm (ICA), a hybrid algorithm of grey wolf optimizer and particle swarm optimization (GWOPSO), the whale optimization algorithm (WOA), and the teaching-learning based optimization algorithm (TLBO), in terms of optimal solutions and operational efficiency. IEO demonstrates outstanding performance in solving SCD problems.
IEEE AccessCOMPUTER SCIENCE, INFORMATION SYSTEMSENGIN-ENGINEERING, ELECTRICAL & ELECTRONIC
CiteScore
9.80
自引率
7.70%
发文量
6673
审稿时长
6 weeks
期刊介绍:
IEEE Access® is a multidisciplinary, open access (OA), applications-oriented, all-electronic archival journal that continuously presents the results of original research or development across all of IEEE''s fields of interest.
IEEE Access will publish articles that are of high interest to readers, original, technically correct, and clearly presented. Supported by author publication charges (APC), its hallmarks are a rapid peer review and publication process with open access to all readers. Unlike IEEE''s traditional Transactions or Journals, reviews are "binary", in that reviewers will either Accept or Reject an article in the form it is submitted in order to achieve rapid turnaround. Especially encouraged are submissions on:
Multidisciplinary topics, or applications-oriented articles and negative results that do not fit within the scope of IEEE''s traditional journals.
Practical articles discussing new experiments or measurement techniques, interesting solutions to engineering.
Development of new or improved fabrication or manufacturing techniques.
Reviews or survey articles of new or evolving fields oriented to assist others in understanding the new area.