apply.OPA: Apply Ordinal Priority Approach (OPA)

In RMCDA: Multi-Criteria Decision Analysis

Apply Ordinal Priority Approach (OPA)

Description

This function applies the Ordinal Priority Approach (OPA) to determine the optimal weights for experts, criteria, and alternatives based on expert opinions, ranks, and criterion importance.

Usage

apply.OPA(expert.opinion.lst, expert.rank, criterion.rank.lst)

Arguments

expert.opinion.lst	A list of matrices where each matrix represents the rankings of alternatives for each criterion as assessed by a particular expert. Each row corresponds to an alternative, and each column corresponds to a criterion.
expert.rank	A numeric vector specifying the rank or weight of importance for each expert.
criterion.rank.lst	A list of numeric vectors where each vector represents the rank or weight of importance for the criteria as assessed by each expert.

Value

A list of matrices where each matrix represents the optimal weights for the alternatives and criteria for a specific expert.

Examples

# Input Data
expert.x.alt <- matrix(c(1, 3, 2, 2, 1, 3), nrow = 3)
colnames(expert.x.alt) <- c("c", "q")
rownames(expert.x.alt) <- c("alt1", "alt2", "alt3")

expert.y.alt <- matrix(c(1, 2, 3, 3, 1, 2), nrow = 3)
colnames(expert.y.alt) <- c("c", "q")
rownames(expert.y.alt) <- c("alt1", "alt2", "alt3")

expert.opinion.lst <- list(expert.x.alt, expert.y.alt)
expert.rank <- c(1, 2)  # Ranks of experts

# Criterion ranks for each expert
criterion.x.rank <- c(1, 2)
criterion.y.rank <- c(2, 1)  # Adjusted criterion rank for expert y
criterion.rank.lst <- list(criterion.x.rank, criterion.y.rank)

# Apply OPA
weights <- apply.OPA(expert.opinion.lst, expert.rank, criterion.rank.lst)

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