This repository contains the MATLAB implementation of the Bayesian Best-Worst Method. You need to have JAGS installed on your machine. See the following link to download JAGS: http://mcmc-jags.sourceforge.net/
For the Python implementation, go to https://colab.research.google.com/drive/1kz7m2lA_cXvA8YvsRNPvgHiSR-GOCEYp. You can simply execute it through your browser without requiring to install anything, though you must have a Google account.
You need to have JAGS installed on your machine. For doing so, follow the steps below:
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Visit the jags development site at http://mcmc-jags.sourceforge.net/ and follow instructions to install the windows version of JAGS.
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In Windows, go to Control Panel, "System and Security", "System", and click on "Advanced System Settings", followed by "Environment Variables" in the "advanced" tab. Under "System variables", click on Path, and add the jags path to the string. This could look something like "C:\Program Files\JAGS\JAGS-3.4.0\x64\bin" or whatever the path is.
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If you have Matlab up and running already, quit MATLAB and start again to make sure that the new path is used by MATLAB.
To run your example, open runme.m and replace the following three variables with your own data
nameOfCriteria: This variable contains the name of Criteria
A_B: contains the best-to-others vectors of all decision-makers. Each row is dedicated to a best-to-others vector from a decision-maker.
A_W: contains the worst-to-other vectors of all decision-makers. Each row is dedicated to an others-to-worst vector from a decision-maker.
Reyhane Fotouhnezhad has made this video on how to set up MATLAB to run an example using Bayesian BWM (the video is in Farsi/Persian language).
If you are interested in making videos on how to set up MATLAB for Bayesian BWM, feel free to reach out, and I will be happy to share it on this page.
If you use this implementation, you can cite our paper: M. Mohammadi, J. Rezaei, Bayesian Best-Worst Method: A Probabilistic Group Decision Making Model, Omega, 2020.
If you have any problem executing the code, contact Majid Mohammadi, majid.mohammadi690@gmail.com