muRty (version 0.3.0)

get_k_best: Murty's algorithm for k-best assignments

Description

Find k-best assignments for a given matrix (returns both solved matrices and costs).

Usage

get_k_best(mat, k_best = NULL, algo = "hungarian", by_rank = FALSE,
  objective = "min", proxy_Inf = 10000000L)

Arguments

mat

Square matrix (N x N) in which values represent the weights.

k_best

How many best scenarios should be returned. If by_rank = TRUE, this equals best ranks.

algo

Algorithm to be used, either 'lp' or 'hungarian'; defaults to 'hungarian'.

by_rank

Should the solutions with same cost be counted as one and stored in a sublist? Defaults to FALSE.

objective

Should the cost be minimized ('min') or maximized ('max')? Defaults to 'min'.

proxy_Inf

What should be considered as a proxy for Inf? Defaults to 10e06; if objective = 'max' the sign is automatically reversed.

Value

A list with solutions and costs (objective values).

Examples

# NOT RUN {
set.seed(1)
mat <- matrix(sample.int(15, 10*10, TRUE), 10, 10)

get_k_best(mat, 3)

# }