GRASPFS: A GRASP algorithm for the permutative flowshop

In jmsallan/combheuristics: Heuristics for combinatorial problems

A GRASP algorithm for the permutative flowshop

Description

A greedy randomized adaptive search procedure (GRASP) for the permutative flowshop. At each iteration, it generates a solution based on the Palmer heuristic. Instead of picking the best element, it picks an element randomly among a restricted candidate list, consisting on the first rcl first elements of the Palmer ordering. Then, this solution is improved with a local search heuristic.

Usage

GRASPFS(M, rcl = 4, iter = 100, op = "swap", opt = "HC", ...)

Arguments

M	A matrix object storing the time to process task j (column) in machine i (row).
rcl	the size of the restricted candidate list.
iter	number of iterations.
op	The neighbourhood operator for the local search heuristic. Presently are implemented swap (the default) and insertion neighbourhoods.
opt	the local search algorithm to implement. Presently are supported HC (hill climbing with HCFS), SA (simulated annealing with SAFS) and TS (tabu search with TSFS).

Value

sol The obtained solution.

obj The makespan of the obtained solution.

Examples

set.seed(2020)
instance <- matrix(sample(10:90, 100, replace=TRUE), 5, 20)
GRASPFS(M=instance)

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