public code v1

2026-05-23 00:32:57 +02:00
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+#' calculateWeights
+#'
+#' Implementation based on https://doi.org/10.1016/j.omega.2015.12.001.
+#' Calculates weights of the criteria using a linear model.
+#' Steps:
+#' 1. Build model (consists of validating model and constructing necessary constraints for LP problem).
+#' 2. Solve LP problem.
+#' 3. Calculate consistency ratio.
+#'
+#' @name calculateWeights
+#' @param criteriaNames Names of the criteria
+#' @param bestToOthers Vector of pairwise comparisons. Best criterion should be 1, others <2, 9>.
+#' @param othersToWorst Vector of pairwise comparisons. Worst criterion should be 1, others <2, 9>.
+#' @return Result that consist of \code{criteriaNames}, \code{criteriaWeights}, \code{consistencyRatio} and a model that was used to calculate weights.
+#' @examples
+#' criteriaNames <- c("quality", "price", "comfort", "safety", "style")
+#' bestToOthers <- c(2, 1, 4, 2, 8)
+#' othersToWorst <- c(4, 8, 2, 4, 1)
+#' calculateWeights(criteriaNames, bestToOthers, othersToWorst)
+#' @import Rglpk
+#' @export
+calculateWeights <- function(criteriaNames, bestToOthers, othersToWorst){
+  model <- buildModel(bestToOthers, othersToWorst, criteriaNames)
+  #const values that are listed in the article
+  consistencyIndex <- c(0, .44, 1.0, 1.63, 2.3, 3., 3.73, 4.47, 5.23)
+
+  #unique optimal solution
+  result <- solveLP(model)
+  weights <- result$solution[1:model$ksiIndex-1]
+  consistencyRatio <- result$solution[model$ksiIndex] / consistencyIndex[as.integer(model$a_bw)]
+
+  result <- list(criteriaNames = criteriaNames, criteriaWeights = weights, consistencyRatio = consistencyRatio)
+  list(result = result, model = model)
+}
+
+solveLP <- function(model){
+  Rglpk_solve_LP(model$objective, model$constraints$lhs, model$constraints$dir, model$constraints$rhs, max = model$maximize)
+}