A multiplicative best–worst method for multi-criteria decision making

2019 ◽  
Vol 47 (1) ◽  
pp. 12-15 ◽  
Author(s):  
Matteo Brunelli ◽  
Jafar Rezaei
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Best Worst Method

A group multi-criteria decision-making based on best-worst method

2018 ◽  
Vol 126 ◽  
pp. 111-121 ◽  
Author(s):  
Soroush Safarzadeh ◽  
Saba Khansefid ◽  
Morteza Rasti-Barzoki
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Best Worst Method

scholarly journals Fusion of BWM and AHP MCDM Methods to Choose the Most Suitable Secondary School for an Individual in the Context of Bangladesh

2019 ◽  
Vol 06 (03) ◽  
pp. 311-328
Author(s):  
N. S. M. Rezaur Rahman ◽  
Md. Abdul Ahad Chowdhury ◽  
Adnan Firoze ◽  
Rashedur M. Rahman
Keyword(s):  
Decision Making ◽  
Secondary School ◽  
Pairwise Comparison ◽  
User Preferences ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Final Score ◽  
Hierarchy Process ◽  
Best Worst Method

Choosing the best schools from a group of schools is a multi-criteria decision-making (MCDM) problem. In this paper, we have represented a method that uses the fusion of two multi-criteria decision-making methods, Best–Worst Method (BWM) and Analytic Hierarchy Process (AHP), to rank some of the user preferred alternatives. The system considers the choice of the user and the quality of the alternatives to rank them. User preferences on the criteria are taken as inputs in the form of best–worst comparison vectors to measure the choice of the user. These values are applied to calculate the numeric weights of each of the criteria. These weights reflect the preference of the user. A dataset of secondary schools in Bangladesh has been compiled and used for automatic quantitative pairwise comparison on the alternatives to calculate the score of each alternative in every criterion, which reflects its quality in that criterion. These scores are calculated using AHP. The weights of the criteria as well as the scores of these alternatives in those criteria are then used to calculate the final score of the alternatives and to rank them accordingly. An extensive experimental analysis and comparative study is reported at the end of this paper.

Selection of sustainable material for the manufacturing of complex automotive products using a new hybrid Goal Programming Model for Best Worst Method–Proximity Indexed Value method

2020 ◽  
pp. 146442072096634
Author(s):  
Saif Wakeel ◽  
Sedat Bingol ◽  
M. Nasir Bashir ◽  
Shafi Ahmad
Keyword(s):  
Decision Making ◽  
Carbon Fiber ◽  
Goal Programming ◽  
Programming Model ◽  
Multi Criteria Decision Making ◽  
Goal Programming Model ◽  
Alternative Materials ◽  
Carbon Fiber Epoxy ◽  
Best Worst Method ◽  
Selection Of

Selection of the most suitable sustainable material to fulfill the requirements of a product in a specific application is a complex task. Material selection problems are basically multi-criteria decision making problems as selection of the optimal material is based on the evaluation of conflicting criteria. Considering the limitations such as ranking reversal problem of the various multi-criteria decision making methods available in the literature, a combination of two recently developed techniques, i.e. the Goal Programming Model for Best Worst Method and Proximity Indexed Value method, is employed in the present study. This hybrid method was used for selection of the best possible material for manufacturing of a complex automobile part for which F1 race car as advanced automotive and its gearbox casing as sensitive part was used. Available alternative materials considered in the present study are alloys of aluminum, magnesium, titanium, and carbon fiber/epoxy laminate. Whereas, criteria affecting gearbox casing’s performance are tensile strength/density, cost, stiffness, damping capacity, thermal conductivity, and sustainable criteria, such as CO2 emission and recycling energy. Goal Programming Model for Best Worst Method is used to determine weights of the criteria and Proximity Indexed Value method is employed for final selection of material. Furthermore, ranking of alternatives was also supported by other multi-criteria decision making methods namely, range of value, weighted product model, simple additive weighting, the technique for order of preference by similarity to ideal solution, a combined compromise solution, and the multi-attributive border approximation area comparison. Membership degree method was also employed to obtain the final optimal ranking of alternative materials from individual results of applied multi-criteria decision making methods. Besides, sensitivity analysis is done to validate reliability of the results and to determine the most critical evaluation criterion. The result of this study revealed that carbon fiber/epoxy laminate is the best alternative material.

scholarly journals A Concentration Ratio for Nonlinear Best Worst Method

2020 ◽  
Vol 19 (03) ◽  
pp. 891-907 ◽  
Author(s):  
Jafar Rezaei
Keyword(s):  
Decision Making ◽  
Nonlinear Model ◽  
Concentration Ratio ◽  
Pairwise Comparison ◽  
Multi Criteria Decision Making ◽  
Comparison System ◽  
Consistency Ratio ◽  
Optimal Weights ◽  
The Relationship ◽  
Best Worst Method

Best Worst Method (BWM) is a multi-criteria decision-making method that is based on a structured pairwise comparison system. It uses two pairwise comparison vectors (best-to-others and others-to-worst) as input for an optimization model to get the optimal weights of the criteria (or alternatives). The original BWM involves a nonlinear model that sometimes results in multiple optimal weights meaning that the weight of each criterion is presented as an interval. The aim of this paper is to introduce a ratio, called concentration ratio, to check the concentration of the optimal intervals obtained from the nonlinear BWM. The relationship between the concentration ratio and the consistency ratio is investigated and it is found that the concentration ratio along with the consistency ratio of the model provides enhanced insights into the reliability and flexibility of the results of BWM.

scholarly journals On solving the Best-Worst Method in multi-criteria decision-making

2018 ◽  
Vol 51 (11) ◽  
pp. 1660-1665 ◽  
Author(s):  
D.J.C. Beemsterboer ◽  
E.M.T. Hendrix ◽  
G.D.H. Claassen
Keyword(s):  
Decision Making ◽  
Multi Criteria Decision Making ◽  
Best Worst Method

scholarly journals Application of Improved Best Worst Method (BWM) in Real-World Problems

Mathematics ◽  
2020 ◽  
Vol 8 (8) ◽  
pp. 1342 ◽  
Author(s):  
Dragan Pamučar ◽  
Fatih Ecer ◽  
Goran Cirovic ◽  
Melfi A. Arlasheedi
Keyword(s):  
Decision Making ◽  
Renewable Energy ◽  
Real World ◽  
Evaluation Criteria ◽  
Decision Makers ◽  
Multi Criteria Decision Making ◽  
Weight Coefficients ◽  
Best Worst Method ◽  
Real World Problems

The Best Worst Method (BWM) represents a powerful tool for multi-criteria decision-making and defining criteria weight coefficients. However, while solving real-world problems, there are specific multi-criteria problems where several criteria exert the same influence on decision-making. In such situations, the traditional postulates of the BWM imply the defining of one best criterion and one worst criterion from within a set of observed criteria. In this paper, an improvement of the traditional BWM that eliminates this problem is presented. The improved BWM (BWM-I) offers the possibility for decision-makers to express their preferences even in cases where there is more than one best and worst criterion. The development enables the following: (1) the BWM-I enables us to express experts’ preferences irrespective of the number of the best/worst criteria in a set of evaluation criteria; (2) the application of the BWM-I reduces the possibility of making a mistake while comparing pairs of criteria, which increases the reliability of the results; and (3) the BWM-I is characterized by its flexibility, which is expressed through the possibility of the realistic processing of experts’ preferences irrespective of the number of the criteria that have the same significance and the possibility of the transformation of the BWM-I into the traditional BWM (should there be a unique best/worst criterion). To present the applicability of the BWM-I, it was applied to defining the weight coefficients of the criteria in the field of renewable energy and their ranking.

scholarly journals How MCDM method and the number of comparisons influence the priority vector

2021 ◽  
pp. 51-51
Author(s):  
Zorica Srdjevic ◽  
Bojan Srdjevic ◽  
Senka Zdero ◽  
Milica Ilic
Keyword(s):  
Decision Making ◽  
Analytic Hierarchy Process ◽  
The Other ◽  
Multi Criteria Decision Making ◽  
Analytic Hierarchy ◽  
Priority Vector ◽  
Mcdm Method ◽  
Comparison Of The Results ◽  
Hierarchy Process ◽  
Best Worst Method

One of the most important issues in multi-criteria decision making is the number of requited judgments decision-maker/analyst has to perform. This paper presents a comparison of the results obtained by standard analytic hierarchy process (AHP), limited AHP and best-worst method (BWM) if the number of criteria is 6, 7, and 8. The examples show that BWM's results are comparable with the results if standard AHP is used, while the limited version of AHP is generally inferior to the other two methods.

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