Addressing uncertainty in closed-loop supply chain networks: a multi-objective approach to integrated production and transportation problems

被引:1
|
作者
Varshney, Niharika [1 ]
Gupta, Srikant [2 ]
Ahmed, Aquil [1 ]
机构
[1] Aligarh Muslim Univ, Dept Stat & Operat Res, Aligarh, Uttar Pradesh, India
[2] Jaipuria Inst Management, Dept Operat & Decis Sci, Jaipur, Rajasthan, India
关键词
Optimization; Sensitivity; Supply chain management; Operations research; HESITANT FUZZY-SETS; DESIGN; OPTIMIZATION; MODEL;
D O I
10.1108/JM2-01-2024-0011
中图分类号
C93 [管理学];
学科分类号
12 ; 1201 ; 1202 ; 120202 ;
摘要
PurposeThis study aims to address the inherent uncertainties within closed-loop supply chain (CLSC) networks through the application of a multi-objective approach, specifically focusing on the optimization of integrated production and transportation processes. The primary purpose is to enhance decision-making in supply chain management by formulating a robust multi-objective model.Design/methodology/approachIn dealing with uncertainty, this study uses Pythagorean fuzzy numbers (PFNs) to effectively represent and quantify uncertainties associated with various parameters within the CLSC network. The proposed model is solved using Pythagorean hesitant fuzzy programming, presenting a comprehensive and innovative methodology designed explicitly for handling uncertainties inherent in CLSC contexts.FindingsThe research findings highlight the effectiveness and reliability of the proposed framework for addressing uncertainties within CLSC networks. Through a comparative analysis with other established approaches, the model demonstrates its robustness, showcasing its potential to make informed and resilient decisions in supply chain management.Research limitations/implicationsThis study successfully addressed uncertainty in CLSC networks, providing logistics managers with a robust decision-making framework. Emphasizing the importance of PFNs and Pythagorean hesitant fuzzy programming, the research offered practical insights for optimizing transportation routes and resource allocation. Future research could explore dynamic factors in CLSCs, integrate real-time data and leverage emerging technologies for more agile and sustainable supply chain management.Originality/valueThis research contributes significantly to the field by introducing a novel and comprehensive methodology for managing uncertainty in CLSC networks. The adoption of PFNs and Pythagorean hesitant fuzzy programming offers an original and valuable approach to addressing uncertainties, providing practitioners and decision-makers with insights to make informed and resilient decisions in supply chain management.
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页数:34
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