An integrated approach for supplier selection in multi-item/multi-supplier environment

Kılıç, Hüseyin Selçuk

doi:10.1016/j.apm.2013.03.010

Cited by 99 publications

(59 citation statements)

References 58 publications

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“…Quality of material [6,21, Price of material [6,21,[26][27][28][29][30][31][33][34][35][36][37][38][39][40][42][43][44][45][46][47][48][49][50][51][52][53][54][55][56] Certification of products [26,31,40,42,44,50,52,57] Delivery time [21,[26][27][28][29][30][31][33][34][35][36]…”

Section: Criteria Referencesmentioning

confidence: 99%

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

et al. 2017

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Supply chain presents a very complex field involving a large number of participants. The aim of the complete supply chain is finding an optimum from the aspect of all participants, which is a rather complex task. In order to ensure optimum satisfaction for all participants, it is necessary that the beginning phase consists of correct evaluations and supplier selection. In this study, the supplier selection was performed in the construction company, on the basis of a new approach in the field of multi-criteria model. Weight coefficients were obtained by DEMATEL (Decision Making Trial and Evaluation Laboratory) method, based on the rough numbers. Evaluation and the supplier selection were made on the basis of a new Rough EDAS (Evaluation based on Distance from Average Solution) method, which presents one of the latest methods in this field. In order to determine the stability of the model and the applicability of the proposed Rough EDAS method, an extension of the COPRAS and MULTIMOORA method by rough numbers was also performed in this study, and the findings of the comparative analysis were presented. Besides the new approaches based on the extension by rough numbers, the results are also compared with the Rough MABAC (MultiAttributive Border Approximation area Comparison) and Rough MAIRCA (MultiAttributive Ideal-Real Comparative Analysis). In addition, in the sensitivity analysis, 18 different scenarios were formed, the ones in which criteria change their original values. At the end of the sensitivity analysis, SCC (Spearman Correlation Coefficient) of the obtained ranges was carried out, confirming the applicability of the proposed approaches.

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Section: Criteria Referencesmentioning

confidence: 99%

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

et al. 2017

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“…Their model is shown to be a good tool for supplier selection decision making situation. Kilic [15] presented a new integrated approach, including fuzzy TOPSIS method and a mixed integer linear programming model, to select suitable supplier in a multi-item/multi-supplier environment. In the first stage of this approach, importance value of each supplier for each product is obtained via fuzzy TOPSIS.…”

Section: Fuzzy Modelsmentioning

confidence: 99%

Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry

2017

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This paper proposes an innovative robust-fuzzy method for multi-objective, multi-period supplier selection problem under multiple uncertainties. This approach integrates robust optimization and fuzzy programming. Uncertain parameters are modeled as random variables that take value within a symmetrical interval. However, due to the complexity or ambiguity of some real world problems and specially the nature of some of the available input data, the length of interval is also highly uncertain. This ambiguity motivated us to present a new approach, which can be applicable to multiple uncertainties conditions. Thus, in our approach the half-length of these intervals is also represented by fuzzy membership function. We develop a model and a solution approach to select suppliers by considering risk. The proposed method is applied to a real case of supplier selection in automobile industry under uncertainty and ambiguity conditions. To verify the proposed model, we evaluated the results by simulation technique and compared values of objective function under different scenarios.

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“…Once the experts use linguistic variable for pair-wise comparison, they are converted to TFN. When the pair-wise comparison matrix is formed, the consistency of the (7,8,9) matrix is tested using consistency index and consistency ratio.…”

Section: Stepmentioning

confidence: 99%

“…As SA quality assessment involves the evaluation of diverse attributes and sub-attributes, it can be considered as a multiple criteria decision making (MCDM) problem. Numerous decisionmaking methods have also been developed and found in the literature [8]. AHP is the commonly used decision-making tool to address MCDM problem and is useful in various real-time applications.…”

Section: Introductionmentioning

confidence: 99%

A Fuzzy Analytical Hierarchy Process (FAHP) Based Software Quality Assessment Model: Maintainability Analysis

Dayanandan¹,

Vivekanandan²

2018

IJIES

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Software quality assessment at the architectural level is efficient because it provides various advantages to find and fix design errors at the earliest stage of software development life cycle (SDLC).Numerous methods have been evolved to validate quality-related issues at the architectural level. The software quality comprises of a total of eight attributes where maintainability is one of the important attribute which affects the overall system quality. Though few methods are available for maintainability analysis, none of the state of art method employs fuzzy logic with Quality Model for Object Oriented Design (QMOOD) metric suite. In this paper, the fuzzy analytic hierarchy process (FAHP) method is proposed with Buckley method to evaluate the influence of maintainability and its subattributes in software quality at the architectural level. The proposed evaluation model is tested against several versions of the MFC and OWL windows application frameworks and the obtained results are compared with the state-of-the-art methods. This experimental analysis shows that the FAHP with Buckley method is superior to the other compared methods.

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An integrated approach for supplier selection in multi-item/multi-supplier environment

Cited by 99 publications

References 58 publications

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

Novel Integrated Multi-Criteria Model for Supplier Selection: Case Study Construction Company

Robust-fuzzy model for supplier selection under uncertainty: An application to the automobile industry

A Fuzzy Analytical Hierarchy Process (FAHP) Based Software Quality Assessment Model: Maintainability Analysis

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