The MCDA package for the R statistical software allows you to use MCDA methods and functions in R.
R(>= 2.1.0), methods, Rglpk, Kendall, glpkAPI

Functions to Support the Multicriteria Decision Aiding Process
Patrick Meyer, Sébastien Bigaret, Richard Hodgett
Functions which can be useful to support the analyst in the Multicriteria Decision Aiding (MCDA) process involving multiple, conflicting criteria.

Patrick Meyer, Sébastien Bigaret, Richard Hodgett, Alexandru-Liviu Olteanu

Rglpk, glpkAPI, methods, RColorBrewer, combinat

Support for the Multicriteria Decision Aiding Process
Support for the analyst in a Multicriteria Decision Aiding (MCDA) process with algorithms,
preference elicitation and data visualisation functions. Sébastien Bigaret, Richard Hodgett, Patrick Meyer,
Tatyana Mironova, Alexandru Olteanu (2017) Supporting the multi-criteria decision aiding process :
R and the MCDA package, Euro Journal On Decision Processes, Volume 5, Issue 1 - 4,
pages 169 - 194 <doi:10.1007/s40070-017-0064-1>.

Rglpk, glpkAPI, methods, RColorBrewer, combinat, triangle,
plyr, ggplot2

Functions to support the Multicriteria Decision Aiding process
MCDA, which stands for Multicriteria Decision Aiding, is an R package implementing functions which can be useful to support the analyst in the decision aiding process involving multiple, conflicting criteria. These functions include, but are not limited to, data pre-processing tools, preference elicitation procedures, aggregation functions, as well as post-processing techniques and data visualisation functions.

MCDA, which stands for Multicriteria Decision Aiding, implements functions which can be useful to support the analyst in the decision aiding process involving multiple, conflicting criteria. These functions include, but are not limited to, data pre-processing tools, preference elicitation procedures, aggregation functions, as well as post-processing techniques and data visualisation functions.

An R implementation of Four Multi-Criteria Decision Making (MCDM) Methods: Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), "VIseKriterijumska Optimizacija I Kompromisno Resenje" (VIKOR), both Multi-Objective Optimization by Ratio Analysis and Full Multiplicative Form (Multi-MOORA) and Weighted Aggregated Sum Product ASsessment (WASPAS). In addition, this package provides a MetaRanking function which combines the output of the previous methods.