In this paper, a new method, called best-worst method (BWM) is proposed to solve multi-criteria decision-making (MCDM) problems. In an MCDM problem, a number of alternatives are evaluated with respect to a number of criteria in order to select the best alternative(s). According to BWM, the best (e.g. most desirable, most important) and the worst (e.g. least desirable, least important) criteria are identified first by the decision-maker. Pairwise comparisons are then conducted between each of these two criteria (best and worst) and the other criteria. A maximin problem is then formulated and solved to determine the weights of different criteria. The weights of the alternatives with respect to different criteria are obtained using the same process. The final scores of the alternatives are derived by aggregating the weights from different sets of criteria and alternatives, based on which the best alternative is selected. A consistency ratio is proposed for the BWM to check the reliability of the comparisons. To illustrate the proposed method and evaluate its performance, we used some numerical examples and a real-word decision-making problem (mobile phone selection). For the purpose of comparison, we chose AHP (analytic hierarchy process), which is also a pairwise comparison-based method. Statistical results show that BWM performs significantly better than AHP with respect to the consistency ratio, and the other evaluation criteria: minimum violation, total deviation, and conformity. The salient features of the proposed method, compared to the existing MCDM methods, are: (1) it requires less comparison data; (2) it leads to more consistent comparisons, which means that it produces more reliable results.

Best-worst multi-criteria decision-making method

This paper briefly reviews the analytic hierarchy process (AHP) and its applications in diverse decision problems. It addresses some of the major extensions and criticisms of the method, as well.

The Analytic Hierarchy Process—A Survey of the Method and its Applications

An overview of the analytic hierarchy process and its applications

The paper considers major principles of application of the multi‐attribute systems to solve legislative tasks. In order to assess dispute resolution methods from economic, social and other points of view, it is necessary to apply methods for assessing solutions according to multiple attributes. All known multi‐attribute methods cannot value the atribute weights as one weight of attribute is higher or lower significant than the other attribute. The new step‐wise weight assessment ratio analysis method (SWARA) allows including experts, lawyers or dispute parties opinion about significance ratio of the attributes in the process of rational decision determination. SWARA method could be applied in practical implementation of specialised decision support systems and alternative dispute resolution in virtual environment. Starting with principles and established approaches, a problem‐structuring methodology was developed which would condition the problem to allow a more thoughtful application of existing...

Selection of rational dispute resolution method by applying new step‐wise weight assessment ratio analysis (Swara)

Fuzzy goal programming- an additive model

Saaty has solved a basic problem in fuzzy set theory using an eigenvector method to determine the weights of belonging of each member to the set. In this paper, a weighted least-square method is utilized to obtain the weights. This method has the advantage that it involves the solution of a set of simultaneous linear algebraic equations and is thus conceptually easier to understand than the eigenvector method. Examples are given for estimating the relative wealth of nations and the relative amount of foreign trade of nations. Numerical solutions are obtained using both the eigenvector method and the weighted least-square method, and the results are compared.

K. Spingarn

Papers

A comparison of two methods for determining the weights of belonging to fuzzy sets