Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry

Banaeian, Narges; Mobli, Hossein; Fahimnia, Behnam; Nielsen, Izabela; Omid, Mahmoud

doi:10.1016/j.cor.2016.02.015

Cited by 404 publications

(244 citation statements)

References 48 publications

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“…Wang et al [21] proposed an integrated MCDM method by combining fuzzy AHP with fuzzy TOPSIS for selecting green suppliers in line with the economic and environmental criteria. Banaeian et al [8] applied three fuzzy MCDM approaches, i.e., fuzzy TOPSIS, fuzzy VIKOR (VlseKriterijuska Optimizacija I Komoromisno Resenje) and fuzzy grey relational analysis (GRA), for green supplier evaluation and selection in the agri-food industry. Tsui et al [22] used a hybrid MCDM method with DEMATEL-based ANP (DANP) and PROMETHEE to appraise and improve the performance of green suppliers in the thin film transistor liquid crystal display industry.…”

Section: Green Supplier Selection Methodsmentioning

confidence: 99%

“…Green supplier selection is a challenging multi-dimensional issue in the competitive environment [8,9], which can be resolved by multi-criteria decision making (MCDM) methods. The QUALIFLEX (qualitative flexible multiple criteria method) [10] is an efficient outranking MCDM method that assesses all possible rankings of considered alternatives and finds the optimum one by using the maximum concordance/discordance index.…”

Section: Introductionmentioning

confidence: 99%

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Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Wang

Liu

et al. 2017

Sustainability

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Nowadays, companies have to improve their practices in the management of green supply chain with increased awareness of environmental issues worldwide. Selecting the optimum green supplier is crucial for green supply chain management, which is a challenging multi-criteria decision making (MCDM) problem. Moreover, while evaluating the performance of alternative suppliers, decision makers tend to determine their assessments using linguistic descriptors due to experts' vague knowledge and information deficiency. Therefore, this paper develops an integrated MCDM model based on the cloud model and QUALIFLEX (qualitative flexible multiple criteria method) approach to assess the green performance of companies under economic and environmental criteria. For the introduced model, the linguistic terms, expressed in normal clouds, are utilized to assess alternatives against each selection criterion. A linear programming model is established to compute the weights of criteria with unknown or incompletely known weight information. An extended QUALIFLEX approach is proposed and used to select the most suitable green supplier. Finally, the proposed green supplier selection method is demonstrated by an empirical example of an auto manufacturer to confirm its rationality and effectiveness.

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Section: Green Supplier Selection Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Wang

Liu

et al. 2017

Sustainability

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“…Furthermore, similar to other MCDM methods, a greater number of VIKOR-employed MCDM papers encompasses supplier selection and performance evaluation models. In this regard, Banaeian et al [129] utilized a hybrid method based on fuzzy TOPSIS, VIKOR, and GRA in order to identify the best supplier within a green agri-food supply chain. Similarly, Prakash and Barua [130] presented a combined model of fuzzy AHP and VIKOR to evaluate and select the best third party logistics provider for an Indian electronics manufacturer.…”

Section: Fuzzy Dematelmentioning

confidence: 99%

Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey

et al. 2017

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Abstract:Growing environmental awareness coupled with stricter governmental regulations has fueled the need for integrating sustainability into supply chain and logistics activities. Accordingly, recent studies in the literature have emphasized the significance of environmentally concerned logistics operations (ECLO). Research in the broad area of ECLO encompasses a wide range of topics including sustainable supply chain, green supply chain, closed-loop supply chain, low-carbon logistics, and waste management. In this paper, a comprehensive content analysis and area review is presented. Over 800 papers published between 1994 and 2017 in peer-reviewed journals, proceedings, and book chapters are utilized. These papers are analyzed in consecutive stages after being reviewed under a structural dimension process that addresses the fields of environmentally concerned logistics operations. Following the state-of-the-art review, a detailed analysis of ECLO research with a special emphasis on fuzzy applications is provided. The findings clearly indicate that the fuzzy multi-criteria decision making technique is a frequently used hybrid method, whereas fuzzy sets theory and other fuzzy hybrid techniques identify a gap in the related literature. This paper provides further critical analysis and other research suggestions in order to clarify these gaps and offer additional research perspectives. This information may provide extensive data that will enable future researchers to fill these gaps within this field.

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“…In the literature there exist a lot of approaches/techniques to solve the problem of sustainable supplier selection but most of the approaches are based on multi-criteria decision making frameworks (Memon, Lee & Mari, 2015;Wang-Chen, Chou, Luu & Yu, 2016;You, You, Liu & Zhen, 2015;Banaeian, Mobli, Fahimnia, Nielsen & Omid, 2016). The fundamental reason for applying the decision making models is that both alternatives and criteria are fixed a priori and that decision happens once.…”

Section: Introductionmentioning

confidence: 99%

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

Hashim

Nazam

Yao

et al. 2017

JIEM

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Abstract:Purpose: The incorporation of environmental objective into the conventional supplier selection practices is crucial for corporations seeking to promote green supply chain management (GSCM).Challenges and risks associated with green supplier selection have been broadly recognized by procurement and supplier management professionals. This paper aims to solve a Tetra "S" (SSSS) problem based on a fuzzy multi-objective optimization with genetic algorithm in a holistic supply chain environment. In this empirical study, a mathematical model with fuzzy coefficients is considered for sustainable strategic supplier selection (SSSS) problem and a corresponding model is developed to tackle this problem.Design/methodology/approach: Sustainable strategic supplier selection (SSSS) decisions are typically multi-objectives in nature and it is an important part of green production and supply chain management for many firms. The proposed uncertain model is transferred into deterministic model by applying the expected value measure (EVM) and genetic algorithm with -188-Journal of Industrial Engineering and Management -https://doi.org/10.3926/jiem.2078 weighted sum approach for solving the multi-objective problem. This research focus on a multiobjective optimization model for minimizing lean cost, maximizing sustainable service and greener product quality level. Finally, a mathematical case of textile sector is presented to exemplify the effectiveness of the proposed model with a sensitivity analysis.Findings: This study makes a certain contribution by introducing the Tetra 'S' concept in both the theoretical and practical research related to multi-objective optimization as well as in the study of sustainable strategic supplier selection (SSSS) under uncertain environment. Our results suggest that decision makers tend to select strategic supplier first then enhance the sustainability. Research limitations/implications:Although the fuzzy expected value model (EVM) with fuzzy coefficients constructed in present research should be helpful for solving real world problems. A detailed comparative analysis by using other algorithms is necessary for solving similar problems of agriculture, pharmaceutical, chemicals and services sectors in future. Practical implications:It can help the decision makers for ordering to different supplier for managing supply chain performance in efficient and effective manner. From the procurement and engineering perspectives, minimizing cost, sustaining the quality level and meeting production time line is the main consideration for selecting the supplier. Empirically, this can facilitate engineers to reduce production costs and at the same time improve the product quality. Originality/value:In this paper, we developed a novel multi-objective programming model based on genetic algorithm to select sustainable strategic supplier (SSSS) under fuzzy environment. The algorithm was tested and applied to solve a real case of textile sector in Pakistan. The experimental results and comparative sensitivity an...

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Green supplier selection using fuzzy group decision making methods: A case study from the agri-food industry

Cited by 404 publications

References 48 publications

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Green Supplier Evaluation and Selection Using Cloud Model Theory and the QUALIFLEX Method

Environmentally Concerned Logistics Operations in Fuzzy Environment: A Literature Survey

Application of multi-objective optimization based on genetic algorithm for sustainable strategic supplier selection under fuzzy environment

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