TSFS: Tabu search heuristic for permutative flowshop

In jmsallan/combheuristics: Heuristics for combinatorial problems

Tabu search heuristic for permutative flowshop

Description

An implementation of a tabu search heuristic for the flowshop.

Usage

TSFS(
  M,
  inisol,
  iter = 100,
  tabu.size = 5,
  op = "swap",
  asp = TRUE,
  eval = FALSE,
  early = FALSE
)

Arguments

M	A matrix object storing the time to process task j (column) in machine i (row).
inisol	The starting solution.
iter	the number of iterations to run (see early parameter).
tabu.size	the length of the tabu list. The tabu list stores the number of tabu moves obtained in the last tabu.size iterations.
asp	if TRUE implements an aspiration condition: if a tabu move has better makespan than the best solution found so far, it is allowed to be considered as candidate solution.
eval	if set to TRUE returns information about the evolution of the algorithm.
early	if set to TRUE, the algorithm stops if it has not improved the solution after iter iterations. For early=TRUE we can set lower values of iter to reduce time of execution.

Value

sol The obtained solution.

obj The makespan of the obtained solution.

evalfit (returned if eval=TRUE) the value of the makespan of the examined solution in each iteration.

evalbest (returned if eval=TRUE) the value of the best solution obtained in each iteration.

Examples

set.seed(2020)
instance <- matrix(sample(10:90, 100, replace=TRUE), 5, 20)
TSFS(M=instance, inisol=PalmerTrapezes(instance)$tra, iter=25, op="insertion", early=TRUE)

jmsallan/combheuristics documentation built on June 22, 2022, 4:11 p.m.