apply.MAUT: Apply Multi-Attribute Utility Theory (MAUT) Method

In RMCDA: Multi-Criteria Decision Analysis

Apply Multi-Attribute Utility Theory (MAUT) Method

Description

Apply Multi-Attribute Utility Theory (MAUT) Method

Usage

apply.MAUT(mat, weights, beneficial.vector, utility.functions, step.size = 1)

Arguments

mat	is a matrix containing values for different properties of different alternatives
weights	are the weights of each property in the decision-making process
beneficial.vector	is a vector containing the column numbers of beneficial properties
utility.functions	is a vector specifying the utility function for each criterion ('exp', 'step', 'quad', 'log', 'ln')
step.size	is a numeric value used for the step utility function (default is 1)

Value

a matrix containing the calculated utility scores

Examples

mat <- matrix(c(75.5, 95, 770, 187, 179, 239, 237, 420, 91), nrow = 3, byrow = TRUE)
weights <- c(0.3, 0.5, 0.2)
beneficial.vector <- c(1, 3)
utility.functions <- c("exp", "log", "quad")
step.size <- 1
result <- apply.MAUT(mat, weights, beneficial.vector, utility.functions, step.size)

RMCDA documentation built on June 8, 2025, 11:14 a.m.