A hybrid MCDM model for resilient supplier selection

Haldar, Anupam; Ray, Amitava; Banerjee, Debamalya; Ghosh, Sampad

doi:10.1080/17509653.2012.10671234

Cited by 54 publications

(37 citation statements)

References 27 publications

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“…It is true that the existing research have shown promising potential of MCDA methods and fuzzy techniques in supplier selection problems (Gan et al, 2019;Haldar et al, 2012Haldar et al, , 2014Hasan, Shohag, Azeem, Paul, & Management, 2015;Jiang, Faiz, & Hassan, 2018). However, there are limitations of the state-of-the-art literatures: (i) to the best of our knowledge, no existing research extends F-MADM framework in supplier evaluation problems leveraging large number of information (time series and graphical information), (ii) no prior study investigated F-MADM approach for evaluating suppliers' performance from resilience and logistics 4.0 perspective, simultaneously, and (iii) it is not clear how fuzzy based TOPSIS can be extended to process inherent uncertainty in decision relevant information associated with both the quantitative and qualitative attributes.…”

Section: Literature Reviewmentioning

confidence: 99%

Resilient supplier selection in logistics 4.0 with heterogeneous information

Hasan

Jiang

Ullah

et al. 2020

Expert Systems with Applications

100

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Supplier selection problem has gained extensive attention in the prior studies. However, research based on Fuzzy Multi-Attribute Decision Making (F-MADM) approach in ranking resilient suppliers in logistic 4.0 is still in its infancy. Traditional MADM approach fails to address the resilient supplier selection problem in logistic 4.0 primarily because of the large amount of data concerning some attributes that are quantitative, yet difficult to process while making decisions. Besides, some qualitative attributes prevalent in logistic 4.0 entail imprecise perceptual or judgmental decision relevant information, and are substantially different than those considered in traditional suppler selection problems. This study develops a Decision Support System (DSS) that will help the decision maker to incorporate and process such imprecise heterogeneous data in a unified framework to rank a set of resilient suppliers in the logistic 4.0 environment.The proposed framework induces a triangular fuzzy number from large-scale temporal data using probability-possibility consistency principle. Large number of non-temporal data presented graphically are computed by extracting granular information that are imprecise in nature. Fuzzy linguistic variables are used to map the qualitative attributes. Finally, fuzzy based TOPSIS method is adopted to generate the ranking score of alternative suppliers. These ranking scores are used as input in a Multi-Choice Goal Programming (MCGP) model to determine optimal order allocation for respective suppliers. Finally, a sensitivity analysis assesses how the Supplier's Cost versus Resilience Index (SCRI) changes when differential priorities are set for respective cost and resilience attributes.

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Section: Literature Reviewmentioning

confidence: 99%

Resilient supplier selection in logistics 4.0 with heterogeneous information

Hasan

Jiang

Ullah

et al. 2020

Expert Systems with Applications

100

View full text Add to dashboard Cite

show abstract

“…The literature on resilient supplier selection is summarized in Table 1. Haldar, Ray, Banerjee and Ghosh [20] developed a resilient supplier selection model using AHP-QFD method to rate the suppliers. They used five resilience criteria (density, complexity, node criticality, responsiveness and re-engineering) for the supplier selection process.…”

Section: Literature Reviewmentioning

confidence: 99%

“…Thus it crucial to provide a reliable level of resilience to the supply side to protect such shortages especially during HILP events [9].Several studies have been conducted to consider resilience in the supply chain [8,10,11]. The concept of resilience in specific to the supplier selection problem has also been discussed by several authors [12][13][14][15][16][17][18][19][20][21][22][23][24][25]. Most of these studies focused on multiple sourcing and operational performance of suppliers.…”

mentioning

confidence: 99%

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

et al. 2019

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Modern supply chains are vulnerable to high impact, low probability disruption risks. A supply chain usually operates in such a network of entities where the resilience of one supplier is critical to overall supply chain resilience. Therefore, resilient planning is a key strategic requirement in supplier selection decisions for a competitive supply chain. The aim of this research is to develop quantitative resilient criteria for supplier selection and order allocation in a fuzzy environment. To serve the purpose, a possibilistic fuzzy multi-objective approach was proposed and an interactive fuzzy optimization solution methodology was developed. Using the proposed approach, organizations can tradeoff between cost and resilience in supply networks. The approach is illustrated using a supply chain case from a garments manufacturing company.

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“…Integrated a new hybrid fuzzy MCDM approach based on the use of DEMATEL, ANP and TOPSIS are then proposed to evaluate the green suppliers. Haldar et al, 2012 AHP, TOPSIS, subjective factor measures (SFM), and objective factor measure (OFM).…”

Section: Tablementioning

confidence: 99%

Developing a novel Grey integrated multi-criteria approach for enhancing the supplier selection procedure: A real-world case of Textile Company

Bakhat¹,

Rajaa²

2019

10.5267/j.dsl

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Supplier selection is one of the most essential activities in purchase management and plays a crucial role in the production phase. Supplier selection as a vital step of supply chain management is a multi-criteria decision-making issue. For any organization, the process of selecting the best supplier holds variable multilayered complications involving quantitative and qualitative criteria. This paper tackles the supplier selection problem in a Turkish Textile Company. The present study carries out a novel grey integrated multi-criteria approach for enhancing the supplier procedure within Textile Company with the help of the grey analytical hierarchy process G-AHP model for weighting the set of criteria, and the grey weighted aggregated sum product assessment WASPAS-G model for prioritizing the suppliers. The study starts with reviewing the previous works of multi-criteria decision-making MCDM methods and the list of existing criteria evaluation in supplier selection. Then, the range of criteria is selected based on the company requirements and the experts' interview. In the case study, the consistency rate of the models is tested in order to verify the quality of experts' judgments. The final results affirm that Grey integrated approach could be efficient and far more precise than the existing models for overcoming the supplier selection and evaluation obstacles in the supply chain management.

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A hybrid MCDM model for resilient supplier selection

Cited by 54 publications

References 27 publications

Resilient supplier selection in logistics 4.0 with heterogeneous information

Resilient supplier selection in logistics 4.0 with heterogeneous information

Interactive Fuzzy Multi Criteria Decision Making Approach for Supplier Selection and Order Allocation in a Resilient Supply Chain

Developing a novel Grey integrated multi-criteria approach for enhancing the supplier selection procedure: A real-world case of Textile Company

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