# TOPSISVector: Implementation of TOPSIS Method for Multi-Criteria Decision... In MCDM: Multi-Criteria Decision Making Methods for Crisp Data

## Description

The `TOPSISVector` function implements the Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) Method with the vectorial normalization prodecure.

## Usage

 `1` ```TOPSISVector(decision, weights, cb) ```

## Arguments

 `decision` The decision matrix (m x n) with the values of the m alternatives, for the n criteria. `weights` A vector of length n, containing the weights for the criteria. The sum of the weights has to be 1. `cb` A vector of length n. Each component is either `cb(i)='max'` if the i-th criterion is benefit or `cb(i)='min'` if the i-th criterion is a cost.

## Value

`TOPSISVector` returns a data frame which contains the score of the R index and the ranking of the alternatives.

## References

Hwang, C.L.; Yoon, K. Multiple Attribute Decision Making. In: Lecture Notes in Economics and Mathematical Systems 186. Springer-Verlag, Berlin, 1981.

## Examples

 ```1 2 3 4``` ``` d <- matrix(c(6,7,10,2,2.75,3.5),nrow = 3,ncol = 2) w <- c(0.5,0.5) cb <- c('min','max') TOPSISVector(d,w,cb) ```

MCDM documentation built on May 29, 2017, 5:41 p.m.