{"title":"A modified neutrosophic fuzzy approach for managing electronic waste considering sustainability and resilience dimensions","authors":"Muhammad Salman Habib , Seung-June Hwang","doi":"10.1016/j.asoc.2025.113097","DOIUrl":null,"url":null,"abstract":"<div><div>The rising problem of electronic waste (e-waste) demands management strategies that minimize environmental impact and prioritize resilience and sustainability, especially amid global disruptions and pressure on manufacturers to adopt extended producer responsibility policies. Existing literature on e-waste management primarily addresses either operational efficiency or sustainability, leaving a research gap in understanding the relationship between sustainability and resilience. To bridge this gap, this study proposes a framework for building resilient and sustainable e-waste management systems in dynamic environments. This framework utilizes a multi-objective optimization model that balances cost, environmental impact, and social factors (sustainability dimensions) while incorporating non-resilience vulnerabilities for optimal decision-making. The model addresses parameter uncertainties through a fuzzy programming approach based on the Me-measure, further enhanced by proposing variants of novel neutrosophic fuzzy programming techniques. The proposed framework is validated by implementing it in a real-world case problem. Key findings show that enhancing e-waste management network resilience relies on strategically reinforcing critical facilities with redundancy. Allocating 100 % priority to resilience achieves a resilience goal of 100 % and a sustainability goal of 52 %, while prioritizing sustainability at 100 % results in a sustainability goal of 73.7 % and resilience of 71.4 %, suggesting that sustainable practices often inherently enhance resilience. Research offers valuable insights for policymakers, regulators, and stakeholders through managerial recommendations, visualizations, and sensitivity analyses.</div></div>","PeriodicalId":50737,"journal":{"name":"Applied Soft Computing","volume":"176 ","pages":"Article 113097"},"PeriodicalIF":7.2000,"publicationDate":"2025-04-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Applied Soft Computing","FirstCategoryId":"94","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1568494625004089","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
The rising problem of electronic waste (e-waste) demands management strategies that minimize environmental impact and prioritize resilience and sustainability, especially amid global disruptions and pressure on manufacturers to adopt extended producer responsibility policies. Existing literature on e-waste management primarily addresses either operational efficiency or sustainability, leaving a research gap in understanding the relationship between sustainability and resilience. To bridge this gap, this study proposes a framework for building resilient and sustainable e-waste management systems in dynamic environments. This framework utilizes a multi-objective optimization model that balances cost, environmental impact, and social factors (sustainability dimensions) while incorporating non-resilience vulnerabilities for optimal decision-making. The model addresses parameter uncertainties through a fuzzy programming approach based on the Me-measure, further enhanced by proposing variants of novel neutrosophic fuzzy programming techniques. The proposed framework is validated by implementing it in a real-world case problem. Key findings show that enhancing e-waste management network resilience relies on strategically reinforcing critical facilities with redundancy. Allocating 100 % priority to resilience achieves a resilience goal of 100 % and a sustainability goal of 52 %, while prioritizing sustainability at 100 % results in a sustainability goal of 73.7 % and resilience of 71.4 %, suggesting that sustainable practices often inherently enhance resilience. Research offers valuable insights for policymakers, regulators, and stakeholders through managerial recommendations, visualizations, and sensitivity analyses.
期刊介绍:
Applied Soft Computing is an international journal promoting an integrated view of soft computing to solve real life problems.The focus is to publish the highest quality research in application and convergence of the areas of Fuzzy Logic, Neural Networks, Evolutionary Computing, Rough Sets and other similar techniques to address real world complexities.
Applied Soft Computing is a rolling publication: articles are published as soon as the editor-in-chief has accepted them. Therefore, the web site will continuously be updated with new articles and the publication time will be short.