Developing of a Novel Integrated MCDM MULTIMOOSRAL Approach for Supplier Selection

Ulutaş, Alptekin; Stanujkić, Dragiša; Karabašević, Darjan; Zavadskas, Edmundas Kazimieras; Smarandache, Florentín; Brauers, Willem K.

doi:10.15388/21-infor445

Cited by 36 publications

(23 citation statements)

References 31 publications

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“…Many MCDM methods [72][73][74][75][76][77][78] have been developed in recent years. PIV is one of the newly developed (by Mufazzal and Muzakkir [15]) MCDM methods and it minimizes the rank reversal problem.…”

Section: Literature Related To Piv Methodsmentioning

confidence: 99%

A New Integrated Grey McDm Model: Case of Warehouse Location Selection

Ulutaş

Balo²,

Sua³

et al. 2021

FU Mech Eng

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Warehouses link suppliers and customers throughout the entire supply chain. The location of the warehouse has a significant impact on the logistics process. Even though all other warehouse activities are successful, if the product dispatched from the warehouse fails to meet the customer needs in time, the company may face with the risk of losing customers. This affects the performance of the whole supply chain therefore the choice of warehouse location is an important decision problem. This problem is a multi-criteria decision-making (MCDM) problem since it involves many criteria and alternatives in the selection process. This study proposes an integrated grey MCDM model including grey preference selection index (GPSI) and grey proximity indexed value (GPIV) to determine the most appropriate warehouse location for a supermarket. This study aims to make three contributions to the literature. PSI and PIV methods combined with grey theory will be introduced for the first time in the literature. In addition, GPSI and GPIV methods will be combined and used to select the best warehouse location. In this study, the performances of five warehouse location alternatives were assessed with twelve criteria. Location 4 is found as the best alternative in GPIV. The GPIV results were compared with other grey MCDM methods, and it was found that GPIV method is reliable. It has been determined from the sensitivity analysis that the change in criteria weights causes a change in the ranking of the locations therefore GPIV method was found to be sensitive to the change in criteria weights.

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Section: Literature Related To Piv Methodsmentioning

confidence: 99%

A New Integrated Grey McDm Model: Case of Warehouse Location Selection

Ulutaş

Balo²,

Sua³

et al. 2021

FU Mech Eng

Self Cite

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“…The proposed model provided a comprehensive and easy approach to the problem. Ulutaş et al [16] developed a novel MULTIMOOSRAL approach to the supplier selection problem. Ulutaş [17] developed a grey MCDM model based on grey Step-wise Weight Assessment Ratio Analysis (SWARA) and Multi-Objective Optimization Method by Ratio Analysis (MOORA) to evaluate the logistics performance of transition economies.…”

Section: Literature Reviewmentioning

confidence: 99%

A Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm in Distribution Center Location Selection: A Case Study in Agricultural Supply Chain

Kieu

Nguyễn

Nguyen

et al. 2021

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Logistics is an important service sector, contributing to improving the competitiveness of the economy. Therefore, along with increasing the application of technology and effective business models, it is necessary to increase the connectivity of the infrastructure systems of industrial parks, roads, and seaports of regions and the country. Over the past decades, Vietnamese businesses have been step-by-step going through many stages from production, packaging, quality, hygiene, and safety to grasping new stages in the domestic and global value chain. In many industries, businesses are increasing the content of their own designs, exploiting brands, and approaching consumption networks in the target market. The role of the distribution center is becoming more and more important in ensuring a seamless and flawless supply chain. In particular, the distribution center is the most sensitive contact point between supply and demand in each enterprise. Therefore, the key mission of a distribution center is to reconcile supply and demand requirements. Distribution center location selection problems usually involve multiple quantitative and qualitative criteria that the decision maker must take into account for assessing the symmetrical impact of the criteria to reach the most accurate result. In this study, the authors propose a hybrid MCDM model based on Spherical Fuzzy Analytic Hierarchy Process (SF-AHP) and Combined Compromise Solution (CoCoSo) Algorithm to support the distribution location selection problem of perishable agricultural products. The proposed model is then applied to the numerical case study of the sweet potato product of the Mekong Delta region of Vietnam to demonstrate the feasibility of the model. The contribution of this research is to propose an MCDM model for improving the efficiency of the agricultural supply chain through selecting a location distribution center. This proposed model can be applied to the agricultural supply chain around the world.

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“…Decision makers introduced many MCDM methods to solve complicated MCDM problems over time, such as ELECTRE [ 7 ], AHP [ 8 ], TOPSIS [ 9 ], COPRAS [ 10 ], VIKOR [ 11 ], MULTIMOORA [ 12 , 13 ], ARAS [ 14 ], WASPAS [ 15 ], and others. In addition to well-known MCDM methods, there are also newly proposed ones such as the EDAS [ 16 ], CODAS [ 17 ], CoCoSo [ 18 ], and MULTIMOOSRAL methods [ 19 ]. A comprehensive overview of the newly proposed MCDM methods, as well as their applications, can be found in Mardani et al [ 20 , 21 ], Hafezalkotob et al [ 22 ], Chandrawati et al [ 23 ], and Liu and Xu [ 24 ].…”

Section: Introductionmentioning

confidence: 99%