version 1.0

DESCRIPTION

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+Package: topsis
+Type: Package
+Title: TOPSIS method for multiple-criteria decision making (MCDM)
+Version: 1.0
+Date: 2013-09-24
+Author: Mahmoud Mosalman Yazdi
+Maintainer: Mahmoud Mosalman Yazdi <m.mosalman@gmail.com>
+Description: Evaluation of alternatives based on multiple criteria using TOPSIS method.
+License: GPL-2
+Packaged: 2013-09-30 17:28:07 UTC; mahmoud
+NeedsCompilation: no
+Repository: CRAN
+Date/Publication: 2013-09-30 20:15:19

MD5

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+35189690043fed76ff83ef5843e6ea5e *DESCRIPTION
+df390c53434517b304ac5db487184641 *NAMESPACE
+224ef24e709b9d691e3c8cc9fd3b1d01 *R/topsis.R
+c9ccb46828d2fcb835b8ce067ddfc1ed *man/topsis.Rd

NAMESPACE

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+exportPattern("^[[:alpha:]]+")

R/topsis.R

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+topsis=function(decision = NULL, weights = NULL, impacts = NULL){
+  if(missing(weights))
+    stop("'weights' must be a numeric vector")
+  if(missing(impacts))
+    stop("'impacts' must be a character vector")
+  if(! is.matrix(decision) |  is.data.frame(decision))
+    stop("'decision' must be a matirx or data frame")
+  if(length(weights) != ncol(decision))
+    stop("length of 'weights' is not equal to number of columns")
+  if(length(impacts) != ncol(decision))
+    stop("length of 'impacts' is not equal to number of columns")
+  if(! all(weights > 0))
+    stop("weights must be positive numbers")
+  if(! is.character(impacts))
+    stop("impacts must be a character vector of '+' and '-' signs")
+  if(! all(impacts == "+" | impacts == "-"))
+    stop("impacts must be only '+' or '-' sign")
+  weights <- weights/sum(weights)
+  N <- matrix(nrow = nrow(decision), ncol = ncol(decision))
+  for(i in 1:nrow(decision)){
+    for(j in 1:ncol(decision)){
+      N[i,j] <- decision[i,j] / sqrt(sum(decision[,j] ^ 2))
+    }
+  }
+  W=diag(weights)
+  V=N%*%W
+  u <- as.integer(impacts == "+") * apply(V, 2, max) + 
+    as.integer(impacts == "-") * apply(V, 2, min)
+  l <- as.integer(impacts == "-") * apply(V, 2, max) + 
+    as.integer(impacts == "+") * apply(V, 2, min)
+  distance_u =function(x){
+    sqrt(sum((x - u) ^ 2))
+  }
+  distance_l =function(x){
+    sqrt(sum((x - l) ^ 2))
+  }
+  du <- apply(V, 1, distance_u)
+  dl <- apply(V, 1, distance_l)
+  score <- dl/(dl+du)
+  return(data.frame(alt.row = 1:nrow(decision), score = score, rank = rank(-score)))
+}

man/topsis.Rd

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+\name{topsis}
+\alias{topsis}
+\title{TOPSIS method for multiple-criteria decision making (MCDM)}
+\description{The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) is a multiple-criteria decision making (MCDM) method.}
+\usage{
+topsis(decision = NULL, weights = NULL, impacts = NULL)
+}
+\arguments{
+\item{decision}{A numeric matrix with m rows for m alternatives and n columns for n criterions.}
+\item{weights}{A numeric vector with length equal to number of columns in decision matrix for weights of criterions.}
+\item{impacts}{A character vector of "+" and "-" signs for the way that each criterion influences on the alternatives.}
+}
+\value{
+A data frame including elements
+\item{alt.row}{ Row number of alternatives in decision matrix. }
+\item{score}{ TOPSIS score of alternatives. }
+\item{rank}{ Rank of alternatives based on TOPSIS scores. }
+}
+\author{Mahmoud Mosalman Yazdi <m.mosalman@gmail.com>}
+\references{
+Yoon, K.P.; Hwang, C. (1995). _Multiple Attribute Decision Making: An Introduction_. California: SAGE publications.
+}
+\examples{
+d <- matrix(rpois(12, 5), nrow = 4)
+w <- c(1, 1, 2)
+i <- c("+", "-", "+")
+topsis(d, w, i)
+}
+\keyword{topsis}