A grey-based rough decision-making approach to supplier selection

Li, Guodong; Yamaguchi, Daisuke; Nagai, Masao

doi:10.1007/s00170-006-0910-y

Cited by 95 publications

(43 citation statements)

References 23 publications

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“…Triangular fuzzy number (TFN) has been the most popular form to present fuzzy numbers which represented with three points;Ã ¼ ðl; m; uÞ. A model based on subjective preferences of a decision-maker is not always accurate as it demands a great deal of knowledge, expertise, and experience (Li, Yamaguchi, & Nagai, 2008). This is where "fuzzy" approaches are used in MCDM problems.…”

Section: Qualitative and Single Source Green Supplier Selectionmentioning

confidence: 99%

Criteria definition and approaches in green supplier selection – a case study for raw material and packaging of food industry

Banaeian

Mobli

Nielsen

et al. 2015

Production & Manufacturing Research

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This paper formulates an integrated framework for deciding about the green supplier selection criteria in food supply chain and also proposes different methods that account for single and multiple sourcing of supplier selection. Green supplier selection relies on green criteria, so determination of suitable set of criteria will affect decision-maker results directly. In this research, an operational model including combination of general and environmental criteria is introduced for green supplier selection criteria in raw material and packaging of food industry. This model reviewed a literature on general and environmental criteria that help us to know and make a set of common green criteria. Afterward, weighting criteria and collecting of sub-criteria are done by an expert team using the Analytic Hierarchy Process and Delphi method. The expert team tried to propose important and practical sub-criteria which are well fitted to food industry. Finally, in the section of supplier selection, two kinds of qualitative and quantitative data are discussed when single and multiple sourcing are required, respectively. Fuzzy Grey Relational Analysis is proposed to ranking suppliers in presence of qualitative and imprecise data. Also linear programming is used to present a model which can select the best suppliers and allocate the orders among them optimally.

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Section: Qualitative and Single Source Green Supplier Selectionmentioning

confidence: 99%

Criteria definition and approaches in green supplier selection – a case study for raw material and packaging of food industry

Banaeian

Mobli

Nielsen

et al. 2015

Production & Manufacturing Research

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“…Hsu et al (2008) evaluated the competencies of various suppliers of a centrifugal pump manufacturer in Taiwan using GRA. Li et al (2008) proposed the grey rough set theory approach for supplier selection. In that approach the linguistic variable assigned to the alternatives were converted into grey number.…”

Section: Overview Of Modelsmentioning

confidence: 99%

Modeling and development of a decision support system for supplier selection in the process industry

Pandian¹,

Venkumar

Rajakarunakaran

2013

J Ind Eng Int

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This paper presents the development of a model based decision support system with a case study on solving the supplier selection problem in a chemical processing industry. For the evaluation and selection of supplier, the analytical hierarchy process (AHP) and grey relational analysis (GRA) were used. The intention of the study is to propose an appropriate platform for process industries in selecting suppliers, which was tested with an electroplating industry during the course of development. The sensitivity analysis was performed in order to improve the robustness of the results with regard to the relative importance of the evaluation criteria and the parameters of the evaluation process. Finally, a practical implementation study was carried out to reveal the procedure of the proposed system and identify the suitable supplier with detailed discussions about the benefits and limitations.

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“…For instance, Wen et al [37] applied RST and a grey model to analyze the factors influencing gas breakdown. Li et al [38] developed a grey-based rough set approach to solve a supplier-selection problem. Thangavel and Pethalakshmi [39] reviewed studies using RST-based feature selection.…”

Section: Basic Concepts Of Rough Set Theorymentioning

confidence: 99%

“…Step 2: RST selects the significant independent variables of a PV system based on its robust reliability in knowledge system [36][37][38][39]. The importance of feature selection based on RST (i.e., core analysis) can be explained as follows [44]: Step 3: The DEA evaluates energy efficiency (i.e., the input/output ratio) of a PV system.…”

Section: The Proposed Hybrid Prediction Modelmentioning

confidence: 99%

Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

Lee

Tong

2012

Energies

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Solar energy has become an important energy source in recent years as it generates less pollution than other energies. A photovoltaic (PV) system, which typically has many components, converts solar energy into electrical energy. With the development of advanced engineering technologies, the transfer efficiency of a PV system has been increased from low to high. The combination of components in a PV system influences its transfer efficiency. Therefore, when predicting the transfer efficiency of a PV system, one must consider the relationship among system components. This work accurately predicts whether transfer efficiency of a PV system is high or low using a novel hybrid model that combines rough set theory (RST), data envelopment analysis (DEA), and genetic programming (GP). Finally, real data-set are utilized to demonstrate the accuracy of the proposed method.

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A grey-based rough decision-making approach to supplier selection

Cited by 95 publications

References 23 publications

Criteria definition and approaches in green supplier selection – a case study for raw material and packaging of food industry

Criteria definition and approaches in green supplier selection – a case study for raw material and packaging of food industry

Modeling and development of a decision support system for supplier selection in the process industry

Predicting High or Low Transfer Efficiency of Photovoltaic Systems Using a Novel Hybrid Methodology Combining Rough Set Theory, Data Envelopment Analysis and Genetic Programming

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