SAFS: Simulated annealing heuristic for permutative flowshop

In jmsallan/combheuristics: Heuristics for combinatorial problems

Simulated annealing heuristic for permutative flowshop

Description

An implementation of a simulated annealing heuristic for the flowshop.

Usage

SAFS(M, inisol, Tmax = 1000, mu = 1, op = "swap", eval = FALSE)

Arguments

M	A matrix object storing the time to process task j (column) in machine i (row).
inisol	The starting solution.
Tmax	the maximum value of temperature, representing the number of iterations of the algorithm.
mu	a parameter tuning the value of probability of selection a solution worse than the presently explored. Higher values of mu reduce the probability of selecting a worse solution.
op	The neighbourhood operator. Presently are implemented swap (the default) and insertion neighbourhoods.
eval	if set to TRUE returns information about the evolution of the algorithm.

Value

sol The obtained solution.

obj The makespan of the obtained solution.

evaltest (returned if eval=TRUE) the value of the tested solution in each iteration.

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)
SAFS(M=instance, inisol=PalmerTrapezes(instance)$tra, Tmax=10000, mu=1000, op="insertion")

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