Promoting Green Supply Chain Management With Optimal Selection Of Packaging Materials Using Integrated Fuzzy MCDM and Rl Model

IF 2.8 4区 生物学 3 Biotech Pub Date : 2023-09-01 DOI:10.46632/ese/2/3/1
{"title":"Promoting Green Supply Chain Management With Optimal Selection Of Packaging Materials Using Integrated Fuzzy MCDM and Rl Model","authors":"","doi":"10.46632/ese/2/3/1","DOIUrl":null,"url":null,"abstract":"Green supply chain management is highly significant to maintain environmental sustainability. The agglomeration of green components enhances and supports the business activities to practice green supply chain more effectively. Utilizing sustainable packaging materials in logistics is a step towards promoting business eco sustainability. This research work attempts to develop a hybrid decision making model by integrating techniques of fuzzy multi criteria decision making (MCDM) and Reinforcement Learning (RL). This research work proposes a decision-making method of IDOCRIW (Integrated Determination of Objective Criteria Weights) under fuzzy environment with linguistic representations to determine the criterion weights of material selection and applies the RL method of Q learning in ranking the packaging materials for promoting green sustainability. The proposed fuzzy based MCDM method resolves the problems of conflict of uncertainty. The ranking results obtained using this method are compared with the non-integrated MCDM method. The proposed combined model shall be discussed under various other extended fuzzy representations. The decision-making problem on optimal selection of packaging materials addressed in this research work benefits the business decision makers to make right choices. This hybrid model will certainly make the logistic environment more robust and also it will upscale the smart framework of supply chain management.","PeriodicalId":48765,"journal":{"name":"3 Biotech","volume":null,"pages":null},"PeriodicalIF":2.8000,"publicationDate":"2023-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"3 Biotech","FirstCategoryId":"5","ListUrlMain":"https://doi.org/10.46632/ese/2/3/1","RegionNum":4,"RegionCategory":"生物学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 0

Abstract

Green supply chain management is highly significant to maintain environmental sustainability. The agglomeration of green components enhances and supports the business activities to practice green supply chain more effectively. Utilizing sustainable packaging materials in logistics is a step towards promoting business eco sustainability. This research work attempts to develop a hybrid decision making model by integrating techniques of fuzzy multi criteria decision making (MCDM) and Reinforcement Learning (RL). This research work proposes a decision-making method of IDOCRIW (Integrated Determination of Objective Criteria Weights) under fuzzy environment with linguistic representations to determine the criterion weights of material selection and applies the RL method of Q learning in ranking the packaging materials for promoting green sustainability. The proposed fuzzy based MCDM method resolves the problems of conflict of uncertainty. The ranking results obtained using this method are compared with the non-integrated MCDM method. The proposed combined model shall be discussed under various other extended fuzzy representations. The decision-making problem on optimal selection of packaging materials addressed in this research work benefits the business decision makers to make right choices. This hybrid model will certainly make the logistic environment more robust and also it will upscale the smart framework of supply chain management.
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
基于模糊MCDM和Rl模型的包装材料优化选择促进绿色供应链管理
绿色供应链管理对保持环境的可持续性具有重要意义。绿色组件的集聚促进和支持企业活动更有效地践行绿色供应链。在物流中使用可持续包装材料是促进商业生态可持续发展的一步。本研究尝试将模糊多准则决策(MCDM)技术与强化学习(RL)技术相结合,建立一种混合决策模型。本研究提出了一种具有语言表征的模糊环境下IDOCRIW (Integrated Determination of Objective Criteria Weights)决策方法来确定材料选择的标准权重,并将Q学习的RL方法应用于促进绿色可持续发展的包装材料排序。提出的基于模糊的MCDM方法解决了不确定性冲突问题。将该方法得到的排序结果与非综合MCDM方法进行了比较。所提出的组合模型将在各种其他扩展模糊表示下进行讨论。本研究所解决的包装材料最优选择的决策问题,有利于企业决策者做出正确的选择。这种混合模式将使物流环境更加稳健,也将提升供应链管理的智能框架。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
3 Biotech
3 Biotech BIOTECHNOLOGY & APPLIED MICROBIOLOGY-
自引率
0.00%
发文量
314
期刊介绍: 3 Biotech publishes the results of the latest research related to the study and application of biotechnology to: - Medicine and Biomedical Sciences - Agriculture - The Environment The focus on these three technology sectors recognizes that complete Biotechnology applications often require a combination of techniques. 3 Biotech not only presents the latest developments in biotechnology but also addresses the problems and benefits of integrating a variety of techniques for a particular application. 3 Biotech will appeal to scientists and engineers in both academia and industry focused on the safe and efficient application of Biotechnology to Medicine, Agriculture and the Environment.
期刊最新文献
Immobilization of alkaline protease produced by Streptomyces rochei strain NAM-19 in solid state fermentation based on medium optimization using central composite design A Predictive Approach for Evaluating Thermo-Physical Properties of Nano fluids Using Artificial Intelligence Algorithms An Assessment on The Manufacturing Environment Using the Grey Relational Analysis Method Identification of Changing Personnel with Double-Layer Network Fusion and Bi-Level Monitoring Mechanism A Smart Neuro-Centric Approach to Predict Heart Attacks for Child Using IOT
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 联系我们:info@booksci.cn
Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。
Copyright © 2023 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1