Upload New File

VIKOR.ipynb

+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": 1,
+   "metadata": {},
+   "outputs": [
+    {
+     "ename": "SyntaxError",
+     "evalue": "invalid syntax (<ipython-input-1-4f8651ffc702>, line 8)",
+     "output_type": "error",
+     "traceback": [
+      "\u001b[1;36m  File \u001b[1;32m\"<ipython-input-1-4f8651ffc702>\"\u001b[1;36m, line \u001b[1;32m8\u001b[0m\n\u001b[1;33m    if(! is.matrix(decision))\u001b[0m\n\u001b[1;37m     ^\u001b[0m\n\u001b[1;31mSyntaxError\u001b[0m\u001b[1;31m:\u001b[0m invalid syntax\n"
+     ]
+    }
+   ],
+   "source": [
+    "VIKOR <- function(decision, #matrix with all the alternatives\n",
+    "                  weights,  #vector with the numeric values of the weights\n",
+    "                  cb,       #vector with the \"type\" of the criteria (benefit = \"max\", cost = \"min\")\n",
+    "                  v         #value with the real number of the 'v' parameter to calculate Q\n",
+    ")\n",
+    "{\n",
+    "  #Checking parameters\n",
+    "  if(! is.matrix(decision))\n",
+    "    stop(\"'decision' must be a matrix with the values of the alternatives\")\n",
+    "  if(missing(weights))\n",
+    "    stop(\"a vector containing n weigths, adding up to 1, should be provided\")\n",
+    "  if(sum(weights) != 1)\n",
+    "    stop(\"The sum of 'weights' is not equal to 1\")\n",
+    "  if(! is.character(cb))\n",
+    "    stop(\"'cb' must be a character vector with the type of the criteria\")\n",
+    "  if(! all(cb == \"max\" | cb == \"min\"))\n",
+    "    stop(\"'cb' should contain only 'max' or 'min'\")\n",
+    "  if(length(weights) != ncol(decision))\n",
+    "    stop(\"length of 'weights' does not match the number of the criteria\")\n",
+    "  if(length(cb) != ncol(decision))\n",
+    "    stop(\"length of 'cb' does not match the number of the criteria\")\n",
+    "  if(missing(v))\n",
+    "    stop(\"a value for 'v' in [0,1] should be provided\")\n",
+    "\n",
+    "  #1. Ideal solutions\n",
+    "  posI <- as.integer(cb == \"max\") * apply(decision, 2, max) +\n",
+    "    as.integer(cb == \"min\") * apply(decision, 2, min)\n",
+    "  negI <- as.integer(cb == \"min\") * apply(decision, 2, max) +\n",
+    "    as.integer(cb == \"max\") * apply(decision, 2, min)\n",
+    "\n",
+    "  #2. S and R index\n",
+    "  norm =function(x,w,p,n){\n",
+    "    w*((p-x)/(p-n))\n",
+    "  }\n",
+    "  SAux <- apply(decision, 1, norm, weights, posI, negI)\n",
+    "  S <- apply(SAux, 2, sum)\n",
+    "  R <- apply(SAux, 2, max)\n",
+    "\n",
+    "\n",
+    "  #3. Q index\n",
+    "  #If v=0\n",
+    "  if (v==0)\n",
+    "    Q <- (R-min(R))/(max(R)-min(R))\n",
+    "  #If v=1\n",
+    "  else if (v==1)\n",
+    "    Q <- (S-min(S))/(max(S)-min(S))\n",
+    "  #Another case\n",
+    "  else\n",
+    "    Q <- v*(S-min(S))/(max(S)-min(S))+(1-v)*(R-min(R))/(max(R)-min(R))\n",
+    "\n",
+    "  #4. Checking if Q is valid\n",
+    "  if( (Q == \"NaN\") || (Q == \"Inf\")){\n",
+    "    RankingQ <- rep(\"-\",nrow(decision))\n",
+    "  }else{\n",
+    "    RankingQ <- rank(Q, ties.method= \"first\") \n",
+    "  }\n",
+    "  #5. Ranking the alternatives\n",
+    "  return(data.frame(Alternatives = 1:nrow(decision), S = S, R = R, Q = Q, Ranking = RankingQ))\n",
+    "\n",
+    "}"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "d <- matrix(c(492.3065182591944 , 45000 , 30.100069992688567,\n",
+    "499.4238816104592 , 45000 , 30.100069992688567,\n",
+    "403.622103782017 , 45000 , 30.100069992688567,\n",
+    "388.2312906158455 , 45000 , 30.100069992688567,\n",
+    "358.77720822367576 , 45000 , 30.100069992688567),\n",
+    "                nrow = 5,ncol = 3)\n",
+    "\n",
+    "w <- c(0.4,0.3,0.3)\n",
+    "cb <- c('min','max','min')\n",
+    "v <- 0.5\n",
+    "\n",
+    "VIKOR(d,w,cb,v)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 2,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "metadata": {},
+   "outputs": [],
+   "source": []
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.7.3"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}