Cluster Analysis for Improving Multiple Criteria Decision Making Analysis [CLUS-MCDA]
This is the only command that need to be written to start the CLUS-MCDA algorithm.
returns a data frame which contains the clustering outputs of classified/categorized data as well as the scores and the four rankings calculated (Ratio System, Reference Point, Multiplicative Form and MUTIMOORA ranking [Dominance Theory]).
 Ijadi Maghsoodi, A., Kavian, A., Khalilzadeh, M., & Brauers, W. K. M. (2018). CLUS-MCDA: A Novel Framework based on Cluster Analysis and Multiple Criteria Decision Theory in a Supplier Selection Problem. Computers & Industrial Engineering, 118 (August 2017), 409<e2><80><93>422. Elsevier. Retrieved from http://linkinghub.elsevier.com/retrieve/pii/S0360835218300962.  Ijadi Maghsoodi, A., Riahi, D., E. Herrera-Viedma, E. K. Zavadskas, An Integrated Parallel Big Data Decision Support Tool Using the W-CLUS-MCDA: A Multi-Scenario Personnel Assessment. [Under-Review].  Ijadi Maghsoodi, A., Riahi, D. The CLUS-MCDA Package: An Original Software Article. [Under-Review]
#just type CLUSMCDA(strt) to run the CLUS-MCDA runnable program/package.
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