Green supplier evaluation in manufacturing systems: a novel interval-valued hesitant fuzzy group outranking approach

Gitinavard, Hossein; Ghaderi, Hossein; Pishvaee, Mir Saman

doi:10.1007/s00500-017-2697-1

Cited by 54 publications

(20 citation statements)

References 52 publications

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“…Therefore, the second and third candidate green suppliers are considered as the best and worst selection, respectively, which is consistent with the results achieved in [67].…”

Section: Comparison and Discussionsupporting

confidence: 85%

“…Furthermore, our proposed method would also be suitable for the real-life scenarios, by comparing with existing methods in the interval-valued environment. For instance, Gitinavard et al [67] introduced a novel interval-valued hesitant fuzzy group outranking approach, which has been proved the feature of practicality for proceeding with the green supplier selection. Here, we utilized the example shown in [67] to carry out the comparative analysis process.…”

Section: Comparison and Discussionmentioning

confidence: 99%

“…For instance, Gitinavard et al [67] introduced a novel interval-valued hesitant fuzzy group outranking approach, which has been proved the feature of practicality for proceeding with the green supplier selection. Here, we utilized the example shown in [67] to carry out the comparative analysis process. In specific, three green suppliers (A 1 , A 2 , and A 3 ) are required to be considered with five criteria which are shown as follows: 1) C 1 : cost; 2) C 2 : quality; 3) C 3 : delivery; 4) C 4 : technology capability; and 5) C 5 : environmental competency.…”

Section: Comparison and Discussionmentioning

confidence: 99%

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A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis

Liu

Xiao

Lin

et al. 2021

IEEE Trans. Syst. Man Cybern, Syst.

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Multicriteria decision analysis evaluates multiple conflicting criteria in decision making, but conflicting criteria are typical in evaluating options. As the existing ordering operations involved in multicriteria decision making cannot easily be implemented with intervals, we assume that scalar representative values with intervals can effectively avoid this issue. To deal with interval-valued criteria, we propose a generalized golden rule representative value approach, which involves the sigmoid function of backpropagation neural networks to tune parameters. Our approach considers the uncertainties and side effects of the interval variables to improve individual scalar representative values. Based on numerical examples, we address the effectiveness of the proposed approach, and we provide a specific application concerning multicriteria decision making with interval criteria satisfaction.

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“…Therefore, the second and third candidate green suppliers are considered as the best and worst selection, respectively, which is consistent with the results achieved in [67].…”

Section: Comparison and Discussionsupporting

confidence: 85%

Section: Comparison and Discussionmentioning

confidence: 99%

Section: Comparison and Discussionmentioning

confidence: 99%

See 1 more Smart Citation

A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis

Liu

Xiao

Lin

et al. 2021

IEEE Trans. Syst. Man Cybern, Syst.

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“…[20][21][22]), stochastic programming models have been developed to address the uncertainty of the problems. Nevertheless, we usually encounter incomplete information in the real world problems [23]. Thus, using the approaches that are capable of modeling the incomplete information is of great importance as far as BSCND is concerned.…”

Section: Introductionmentioning

confidence: 99%

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

Babazadeh

Ghaderi

Pishvaee

2019

Computers & Chemical Engineering

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This paper proposes a possibilistic programming model in order to design a second-generation biodiesel supply chain network under epistemic uncertainty of input data. The developed model minimizes the total costs of the supply chain from supply centers to the biodiesel and glycerin consumer centers. Waste cooking oil and Jatropha plants, as non-edible feedstocks, are considered for biodiesel production. To cope with the epistemic uncertainty of the parameters, a credibility-based possibilistic programming approach is employed to convert the original possibilistic programming model into a crisp counterpart. An accelerated benders decomposition algorithm using efficient acceleration mechanisms is devised to deal with the computational complexity of solving the proposed model in an efficient manner. The performance of the proposed possibilistic programming model and the efficiency of the developed accelerated benders decomposition algorithm are validated by performing a computational analysis using a real case study in Iran.

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“…Based on group decision analysis, Darabi and Heydari [40] presented an interval-valued hesitant fuzzy ranking method for selecting green suppliers. Gitinavard et al [41] developed a unique interval-valued hesitant fuzzy group outranking method for choosing green suppliers. Qin et al [42] recommended a comprehensive MCGDM approach for GSS in interval type-2 fuzzy sets.…”

Section: Introductionmentioning

confidence: 99%

A Multi-Criteria Group Decision Making Model for Green Supplier Selection under the Ordered Weighted Hesitant Fuzzy Environment

2018

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The green supplier selection (GSS) problem is one of the most pressing issues that can directly affect manufacturer performance. GSS has been studied in previous literature, which is considered to be a typical multiple criteria group decision making (MCGDM) problemThe ordered weighted hesitant fuzzy MCGDM method can present the importance of each possible value, and the priority relationship among criteria has rarely been studied. In this study, we first extend the prioritized average (PA) operator to the ordered weighted hesitant fuzzy set (OWHFS) for solving the both problems. The generalized ordered weighted hesitant fuzzy prioritized weighted average operator (GOWHFPWA) is recommended, and some desirable properties are discussed. Based on this operator, a novel MCGDM method for GSS is developed. A numerical example of GSS is then given to prove the robustness of the proposed approach, and a sensitivity analysis is used to identify the robustness of the proposed method. Finally, a comparative analysis based on the MCGDM approach with the hesitant fuzzy prioritized weighted average (HFPWA) operator is illustrated to indicate the validity and advantages of the proposed approach.

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Green supplier evaluation in manufacturing systems: a novel interval-valued hesitant fuzzy group outranking approach

Cited by 54 publications

References 52 publications

A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis

A Generalized Golden Rule Representative Value for Multiple-Criteria Decision Analysis

A benders-local branching algorithm for second-generation biodiesel supply chain network design under epistemic uncertainty

A Multi-Criteria Group Decision Making Model for Green Supplier Selection under the Ordered Weighted Hesitant Fuzzy Environment

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