solver_cuckoo: Cuckoo Search Solver (Toda Version)

Description Usage Arguments Details Value References

View source: R/solver_cuckoo.R

Description

Solves a instance of the 3-GCP problem using the Cuckoo Search (CS) implementation described in Toda et al., 2016.

Usage

1

Arguments

G

the graph to be solved, represented by a list where G$V is the number of nodes, and G$E is a |E|x2 matrix of edges.

nfe

the number of function evaluations. The solver will stop after this number has been exceeded.

args

a list with arguments for the method. The list must contain the following names:

  • pop: Integer > 0. The size of the solution set X

  • pc: Float in [0,1]. The probability of mutation in step 2.

  • compare: Boolean. Wheter the individuals in step 2 are compared before being accepted.

  • policy: One of "levy", "uniform", "fixed". Whether the m value in step 2 is chosen from a levy distribution, uniform distribution or a fixed value.

  • E: Value of 'm' for policy = "fixed"

  • beta: Parameter for the levy distribution

  • alpha: Parameter for the levy distribution

Details

The CS algorithm begins with a random set of solutions X, and at every iteration performs the following two steps:

Mutate.cuckoo(x_i, policy) generates a new individual as follows: an integer 'm' is chosen based on the policy parameter (levy distribution, uniform distribution, or fixed). Then 'm“ elements from x_i are changed to a random, different value.

Value

A list with three names:

References

Toda Keita, Claus Aranha, Hitoshi Kanoh, "Solving the Graph Coloring Problem using Cuckoo Search", Technical Report of the Information Processing Society of Japan, 2016


caranha/EvoGCP documentation built on May 3, 2021, 3:40 p.m.