A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model

Zolfani, Sarfaraz Hashemkhani; Chatterjee, Prasenjit; Yazdani, Morteza

doi:10.3846/cibmee.2019.081

Cited by 23 publications

(13 citation statements)

References 21 publications

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“…CoCoSo method is one of the MCDM methods, and was developed by Yazdani et al [24]. CoCoSo consists of two commonly used methods, SAW and EWP [72]. From this point of view, the ranking results of alternatives obtained from the method can be considered as a summary or presentation of compromise solutions [25].…”

Section: Cocoso Methodsmentioning

confidence: 99%

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Adalı¹,

Çağlar²

2023

Pamukkale J Eng Sci

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Scholarships for the students are the financial supports provided by the government or institutions. There may be a great number of competing applicants with the knowledge, skills and abilities to successfully fulfill the scholarship needs. So, it is difficult to select the most suitable students among multiple applicants for these providers. In this study, scholarship students' selection is handled as a complex decision making problem, and this problem is solved by integration of two Multi Criteria Decision Making (MCDM) methods, Best-Worst Method (BWM) and COmbined COmpromise SOlution (CoCoSo). In order to demonstrate the applicability of these methods to the scholarship student selection problem, a real problem is solved. This problem is designed as a group decision making problem, and BWM, the improved Analytic Hierarchy Process method, is employed to derive the criteria weights. A solution to the problem where decision makers' best and worst criteria are not common and unique is suggested. On the other hand, CoCoSo method is used for the ranking purposes of the applicants. The novelty of this study is that scholarship selection problem is solved with BWM and CoCoSo methods for the first time. The integrated usage of BWM and CoCoSo methods is thought as suitable and effective methods to rank or select the best candidate or alternative among a number of candidates or alternatives because of satisfactory results. Öğrencilere yönelik burslar, devlet veya kurumlar tarafından sağlanan mali desteklerdir. Sağlanan bursun gerekliliklerini başarıyla yerine getirmek için gerekli olan bilgi, beceri ve yeteneklere sahip çok sayıda rakip öğrenci olabilir. Bu nedenle, burs sağlayıcılar için birden fazla başvuru arasından en uygun öğrencileri seçmek zordur. Bu çalışmada, burs seçimi karmaşık bir karar verme problemi olarak ele alınmış ve bu problem, Çok Kriterli Karar Verme (ÇKKV) yönteminlerinden olan En İyi-En Kötü Yöntemi (BWM) veBirleşik Uzlaşma Çözümü (CoCoSo yöntemi) birlikte kullanılarak çözülmüştür. Bu yöntemlerin burslu öğrenci seçme problemine uygulanabilirliği, gerçek bir problemin çözümü ile gösterilmiştir. Problem, grup karar verme problemi olarak tasarlanmıştır. Problemde kriterlerin ağırlıkları, Analitik Hiyerarşi Süreci yönteminin geliştirilmiş bir hali olan BWM ile hesaplanmıştır. Aynı zamanda, karar vericilerin en iyi ve en kötü kriterlerinin ortak ve tek olmadığı probleme bir çözüm önerilmiştir. Öte yandan, başvuran adayların sıralamaları için CoCoSo yöntemi kullanılmıştır. Bu çalışma ile bursiyer seçim problem, ilk kez BWM ve CoCoSo yöntemleri ile çözülmüştür. Çalışmadan elde edilen tatmin edici sonuçlar, bir dizi aday veya alternatif arasından en iyi adayı veya alternatifi sıralamak ya da seçmek için BWM ve CoCoSo yöntemlerinin birlikte kullanımının uygun ve etkili bir yaklaşım olacağını göstermektedir.

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Section: Cocoso Methodsmentioning

confidence: 99%

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Adalı¹,

Çağlar²

2023

Pamukkale J Eng Sci

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“…The CoCoSo has been used in different research fields as an effective method for ordering the criteria. For sustainable supplier selection problems, Zolfani et al [69] suggested a BWM-CoCoSo. A hybrid MCDM model has been proposed based on the fuzzy SWARA and CoCoSo method [70].…”

Section: Cocoso Methodsmentioning

confidence: 99%

Evaluation of Wind Turbine Failure Modes Using the Developed SWARA-CoCoSo Methods Based on the Spherical Fuzzy Environment

et al. 2022

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Accurately recognizing potential failures in the early stages of providing products or services can prevent the loss of investment and time and reduce the risk of safety hazards. Failure mode and effects analysis (FMEA) is a conventional approach for detecting and prioritizing the probable failures of a product's design or production process. Nevertheless, the traditional risk priority number (RPN) method has come under criticism for its deficiencies. This paper proposes a modified FMEA method based on fuzzy Multi-Criteria Decision Making (MCDM) techniques to cope with the weaknesses of the previous methodologies and improve the primary method. The concept of spherical fuzzy sets (SFS) is utilized to address the vagueness and impreciseness of the information that allows the experts to have more freedom in making decisions by including membership, non-membership, and hesitation of fuzzy sets. Initially, the procedure of assigning weights to the RPN criteria is implemented with SFS step-wise weight assessment ratio analysis (SWARA). Then, the failure modes are ranked by the SFS combined compromise solution (CoCoSo) method. The effectiveness and practicality of the suggested approach are illustrated through a case study on the Manjil wind farm in Iran. Results show that the suggested model is more reliable and realistic to be utilized in the prioritization of failures than the common FMEA method or other integrated MCDM approaches.

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“…Erceg et al [65] coupled the ABC analysis, FUCOM criteria weighting method, and an interval rough CoCoSo method to rank suppliers for three inventory classes. Hashemkhani Zolfani et al [66] developed a BWC-CoCoSo approach to solve the sustainable supplier selection problem for a steel company. Karaşan and Bolturk [67] proposed an interval neutrosophic CoCoSo method to rank solid waste disposal sites.…”

Section: Applications and Extensions Of The Cocoso Methodsmentioning

confidence: 99%

Picture Fuzzy Decision-Making Approach for Sustainable Last-Mile Delivery

et al. 2020

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In light of the increasing importance of last-mile delivery (LMD) and the associated high costs, air pollution, and logistical challenges, research on sustainable LMD is highly trending and dynamic. The selection of sustainable LMD mode is an emerging problem for decision-makers in the logistics industry. The key question is how to determine the best LMD mode from a set of alternatives under numerous criteria with ambiguous, vague, and uncertain sustainability-related information. This paper aims to provide an advanced decision-making approach for sustainable LMD. Firstly, 20 sustainable LMD mode evaluation criteria are identified. Secondly, picture fuzzy sets (PFSs) are exploited to help decision-makers to more naturally express their preferences by voting. Thirdly, a hybrid picture fuzzy criteria weighting method based on the Direct rating and R-norm entropy is developed to compute the importance of evaluation criteria. Fourthly, a novel picture fuzzy Combined Compromise Solution method is formulated to rank alternative LMD modes. Fifthly, the presented picture fuzzy approach for sustainable LMD is implemented in the real-life decision-making context. The results show that "e-cargo bike" is the best alternative in the Pardubice context. The comparative analysis with three state-of-the-art PFS-based MCDM methods approved the high reliability of the provided approach. The sensitivity analyses of the trade-off parameter and balancing factor confirmed the high robustness of the presented approach. The introduced approach can help decision-makers in the logistics industry to elucidate sustainable LMD mode. It can solve not only the highlighted problem but also other MCDM problems under the picture fuzzy environment.

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A structured framework for sustainable supplier selection using a combined BWM-CoCoSo model

Cited by 23 publications

References 21 publications

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Group decision making in best-worst method when the best and worst are not unique: case study of scholar selection

Evaluation of Wind Turbine Failure Modes Using the Developed SWARA-CoCoSo Methods Based on the Spherical Fuzzy Environment

Picture Fuzzy Decision-Making Approach for Sustainable Last-Mile Delivery

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