Best-worst multi-criteria decision-making method

By Jafar Rezaei. 2015

3,831 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Control and Systems Engineering, Management Science and Operations Research

View Paper: https://www.semanticscholar.org/paper/6723625d082292858d867b823185afc793200472

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

In Control and Systems Engineering

In Management Science and Operations Research

Citations in the corpus

A New Model for Determining Weight Coefficients of Criteria in MCDM Models: Full Consistency Method (FUCOM) (2018, methodology): “Through the examples from the References [14,118,130,144–149] tested so far, FUCOM has showed a high consistency of the results, since the DFC values have been approximately equal to zero (DFC ≈ 0).”
Measuring the relative importance of the logistics performance index indicators using Best Worst Method (2018, methodology): “Two different models have been proposed for BWM, the former of which (Rezaei, 2015) could lead to multiple optimal solutions, while the latter (Rezaei, 2016) aims at finding unique weights.”
ZBWM: The Z-number extension of Best Worst Method and its application for supplier development (2018, methodology): “Eight criteria for capabilities dimension and four criteria for willingness dimension proposed by Rezaei (2015) are shown in Tables 6 and 7.”
Selection of biomass thermochemical conversion technology in the Netherlands: A best worst method approach (2017, methodology): “Here we present the five steps of the linear BWM (Rezaei, 2015, 2016): Step 1 Determining a set of criteria.”
A Modified TOPSIS Method Based onDNumbers and Its Applications in Human Resources Selection (2016, methodology): “And there are many other methods, such as best worst method [9], characteristic objects method [10], fuzzy setsmethod [11–13], rough sets [14], and analytic hierarchy process [15–17].”
Modification of the Best-Worst and MABAC methods: A novel approach based on interval-valued fuzzy-rough numbers (2018, methodology): “Since the method is very recent, the literature so far only has the traditional (crisp) BWM (Rezaei, 2015; Rezaei et al., 2015; Rezaei, 2016; Gupta, 2017; Shojaei et al., 2017; Ren et al., 2017; Wan Ahmad et al., 2017) and modification of the BWM carried out using fuzzy numbers (Guo and Zhao, 2017;…”
A supply chain sustainability innovation framework and evaluation methodology (2018, methodology): “General steps involved in this technique include (Rezaei 2015, 2016): Step 1: Finalisation of decision criteria.”