Sustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making

MakaleYalnız künyeScopus SJRQ1
  • SDG 9 · Sanayi, Yenilikçilik ve Altyapı
  • SDG 12 · Sorumlu Üretim ve Tüketim

Özet

Supplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier's performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier's ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.

Anahtar Kelimeler

RDL Kalıcı Bağlantı (PID)
https://rdlopen.rawdatalibrary.net/r/munzur/2864Resmi atıflarda kullanılan kalıcı adres
DOI
https://doi.org/10.1016/j.cie.2021.107756Yayıncı resmi DOI adresi
İndeks kayıtları
Kaydın indeks veri tabanlarındaki sayfası (aktarımda alınan kayıt numarasıyla). Erişim, indeksin kendi koşullarına bağlıdır.
Atıflar
Scopus
67
WoS
56
OpenAlex
64
Her kaynağın kendi saydığı toplam atıf; aktarım ve zenginleştirme sırasında alındı.
Tam Kayıt
AlanDeğerDil
dc.contributor.authorLo, Huai-Wei
dc.contributor.authorLiaw, Ching-Fang
dc.contributor.authorGul, Muhammet
dc.contributor.authorLin, Kuan-Yu
dc.date.accessioned2026-10-28T14:55:54.438325232Z
dc.date.available2026-10-28T14:55:54.438325232Z
dc.date.issued2021
dc.description.abstractSupplier selection and transportation planning are essential tasks in managing supply chain networks (SCNs). The choice of a supplier has a significant influence on the transportation planning of SCNs, as the transportation routes will change. A limited number of studies in the literature have addressed the supplier selection and transportation planning issues simultaneously. This study proposes a two-stage multi-criteria decision-making (MCDM) approach for sustainable supplier evaluation and transportation planning in multi-level SCNs. Initially, a supplier evaluation framework is proposed using the modified indifference threshold-based attribute ratio analysis (ITARA) and the performance calculation technique of the integrated multiple multi-attribute decision-making (PCIM-MADM) to determine the supplier's performance index. Subsequently, a multi-level SCN model is established, and the sustainable supplier selection and transportation planning problem is solved by the fuzzy multi-objective linear programming (FMOLP) method. A set of real-world data provided by a smart audio manufacturing company has been used to demonstrate the proposed approach. Decision-makers understand the importance of criteria through the weights constructed by the modified ITARA. Moreover, the results of the PCIM-MADM can effectively determine the supplier's ranking and provide improving strategies for underperforming suppliers. The augmented max–min technique of the FMOLP can produce a single optimal solution of the transportation allocation. The results show that our approach can effectively evaluate sustainable supplier performance and optimize transportation planning in SCNs.
dc.identifier.articlenumber107756
dc.identifier.doi10.1016/j.cie.2021.107756
dc.identifier.eissn1879-0550
dc.identifier.issn0360-8352
dc.identifier.scopus2-s2.0-85117686263
dc.identifier.urihttps://rdlopen.rawdatalibrary.net/r/munzur/2864
dc.identifier.volume162
dc.identifier.wosWOS:000720348400006
dc.language.isoen
dc.publisherElsevier Ltd
dc.relation.ispartofComputers and Industrial Engineering
dc.rightsinfo:eu-repo/semantics/closedAccess
dc.subjectManufacturing
dc.subjectMCDM
dc.subjectSupplier selection
dc.subjectSupply chain network
dc.subjectSustainable
dc.subjectTransportation planning
dc.subject.classificationComputer Science, Interdisciplinary Applications
dc.subject.classificationEngineering, Industrial
dc.subject.classificationComputer Science
dc.subject.classificationEngineering
dc.subject.otherDecision making
dc.subject.otherLinear programming
dc.subject.otherSupply chains
dc.subject.otherTransportation routes
dc.subject.otherMulti criteria decision-making
dc.subject.otherMulticriteria decision-making
dc.subject.otherMulticriterion decision makings
dc.subject.otherMultilevels
dc.subject.otherRatio analysis
dc.subject.otherSupplier Evaluations
dc.subject.otherSupplier selection
dc.subject.otherSupply chain network
dc.subject.otherSustainable
dc.subject.otherTransportation planning
dc.subject.otherManufacture
dc.titleSustainable supplier evaluation and transportation planning in multi-level supply chain networks using multi-attribute- and multi-objective decision making
dc.typeArticle
rdl.citation.openalex64
rdl.citation.scopus67
rdl.citation.wos56
rdl.oa.statusclosed
rdl.scopus.quartileQ1
rdl.sdgSDG09
rdl.sdgSDG12
rdl.source.indexSCOPUS
rdl.source.indexWOS
rdl.wos.indexScience Citation Index Expanded (SCI-EXPANDED)