Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Hasan, Md. Gulzarul; Ashraf, Zubair; Khan, Mohammad Faisal

doi:10.1002/int.22663

Cited by 19 publications

(17 citation statements)

References 81 publications

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“…In this article, the intelligent programming education of Chinese university education management is studied. By making relevant policies, changing teaching methods and using spare time, the problems existing in university programming education are solved and the teaching effect is optimized [12,13].…”

Section: Introductionmentioning

confidence: 99%

University Education Management Model Based on Artificial Intelligence Programming and Analysis Technology Foundation for Building Models and Applications

Huang

2022

Mobile Information Systems

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The reform and development of university education management are operating according to their own laws with the changes of the internal environment of education and the social external environment such as politics, economy, science and technology, and culture. As a branch of the mechanism of university education management, the operation mechanism of university education management supports the reform and development of university education management. This article studies the construction of a university education management model based on an intelligent programming analysis method. The research shows that the average score of the control class before the experiment is 63.7748 and the average score of the experimental class is 63.8954. It can be seen that the average score difference between the two classes is only 0.1206. Understand the performance changes of various dynamic forces by gradually contacting complex structures. Through building + intelligent programming, we can preliminarily understand programming and increase children’s interest in programming; strengthen programming ability; learn various complex structures; and lay a good foundation for later intelligent programming. This article studies the intelligent programming education of university education management and solves the problems existing in University Programming Education by formulating relevant policies, changing teaching methods and using after-school time, so as to optimize the teaching effect.

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Section: Introductionmentioning

confidence: 99%

University Education Management Model Based on Artificial Intelligence Programming and Analysis Technology Foundation for Building Models and Applications

Huang

2022

Mobile Information Systems

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“…BO and OW) are treated as the inputs to a linear programming model, which is finally solved to determine the optimal criteria weight values. As this method is based on only the best and the worst criteria for pair-wise comparisons, it requires fewer computational steps, while providing a clear understanding of the evaluation process, and more consistent and unbiased results (Sadjadi and Karimi, 2018;Pamučar et al, 2020;Khan et al, 2021;Rodríguez-Gutiérrez et al, 2021;Hasan et al, 2022;Srdjevic et al, 2022).…”

Section: Irn-bwmmentioning

confidence: 99%

An integrated IRN-BWM-EDAS method for supplier selection in a textile industry

Paul

Chakraborty

2022

Decis. Mak. Appl. Manag. Eng.

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Like all other manufacturing industries, supplier selection also plays a pivotal role in a textile industry with respect to timely and cost-effective delivery of raw materials (cotton, yarn or fabric), chemicals and dyes, machineries, spare parts and other auxiliary parts/items. An appropriately selected supplier would help the textile industry in seamless production of final or semi-finished products leading to effective deployment of supply chain management concept. Due to involvement of many competing suppliers and a set of conflicting criteria, supplier selection is often treated as a typical multi-criteria decision making problem. The process of choosing the right supplier for a given item often becomes more difficult due to presence of both quantitative and qualitative evaluation criteria. In this paper, based on six most significant criteria, an attempt is put forward to integrate interval rough number (IRN) with best worst method (BWM) and evaluation based on distance from average solution (EDAS) method to solve a supplier selection problem for a textile industry. The application of IRN helps in expressing opinions of the decision makers with respect to relative importance of the considered criteria and performance of the suppliers against each of the criteria using rough boundary intervals under group decision making environment. Later, the criteria weights are determined using IRN-BWM and the alternative suppliers are ranked from the best to the worst employing IRN-EDAS method. An IRN Dombi weighted geometric averaging (IRNDWGA) technique is considered to aggregate the opinions of the decision makers. This integrated approach identifies alternative 3 as the most apposite supplier for the textile industry under consideration.

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“…To handle multiple values for the strength of importance of criterion i over j, recently, a novel extension of the best-worst method WAS proposed by Hasan et al [28], known as the multichoice best-worst method (MCBWM). The basis of the method is multichoice mathematical programming [29,30], where multiple choices are associated with parameters.…”

Section: Introductionmentioning

confidence: 99%

“…In BWM. Hasan et al [28] considered multiple choices in pairwise comparisons. By demonstrating the ability of the proposed MCBWM to handle numerous choices offered by the decision maker for pairwise comparisons, they demonstrated an improvement over the BWM.…”

Section: Introductionmentioning

confidence: 99%

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A Group Decision-Making Approach in MCDM: An Application of the Multichoice Best–Worst Method

2023

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Multicriteria decision-making (MCDM) techniques have successfully been used to address a wide range of real-world decision-making issues. The best–worst method (BWM) is one of the several deterministic MCDM approaches. A recently proposed method called the multichoice best–worst method (MCBWM) takes into account several linguistic terms for pairwise comparisons of relative preferences among the criteria. It has been shown that the MCBWM approach has advantages over BWM: it reduces the calculation and determines optimal weight values by providing the choices for the optimal solution. This paper proposes a unique method for group decision-making based on MCBWM. We extended the MCBWM to solve group decision-making problems. A novel solution approach was developed and validated for multiple problems. Two examples and one case study were solved using the proposed approach to demonstrate the validity and application of the proposed method. The results were further compared with existing models to validate the proposed approach. We found that the obtained ranking order for all problems is the same and that the proposed model has a higher consistency ratio than the existing approaches. This method can be extended to other mathematical programming models for collective decision making in uncertain situations.

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Multi‐choice best‐worst multi‐criteria decision‐making method and its applications

Cited by 19 publications

References 81 publications

University Education Management Model Based on Artificial Intelligence Programming and Analysis Technology Foundation for Building Models and Applications

University Education Management Model Based on Artificial Intelligence Programming and Analysis Technology Foundation for Building Models and Applications

An integrated IRN-BWM-EDAS method for supplier selection in a textile industry

A Group Decision-Making Approach in MCDM: An Application of the Multichoice Best–Worst Method

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