get_k_best: Murty's algorithm for k-best assignments

In muRty: 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

set.seed(1)
mat <- matrix(sample.int(15, 10*10, TRUE), 10, 10)

get_k_best(mat, 3)

muRty documentation built on Feb. 29, 2020, 5:08 p.m.