parsimony_Crossover: Crossover operators in GA-PARSIMONY

In jpison/GAparsimony: Searching Parsimony Models with Genetic Algorithms

Crossover operators in GA-PARSIMONY

Description

Functions implementing particular crossover genetic operator for GA-PARSIMONY. Method uses for model parameters Heuristic Blending and random swapping for binary selected features.

Usage

parsimony_crossover(object, parents, alpha=0.1, perc_to_swap=0.5, ...)

Arguments

object	An object of class "ga_parsimony", usually resulting from a call to function ga_parsimony.
parents	A two-rows matrix of values indexing the parents from the current population.
alpha	A tuning parameter for the Heuristic Blending outer bounds [Michalewicz, 1991]. Typical and default value is 0.1.
perc_to_swap	Percentage of features for swapping in the crossovering process.
...	Further arguments passed to or from other methods.

Value

Return a list with two elements:

children	Matrix of dimension 2 times the number of decision variables containing the generated offsprings;
fitnessval	Vector of length 2 containing the fitness validation values for the offsprings. A value NA is returned if an offspring is different (which is usually the case) from the two parents.
fitnesstst	Vector of length 2 containing the fitness with the test database (if it was supplied), for the offsprings. A value NA is returned if an offspring is different (which is usually the case) from the two parents.
complexity	Vector of length 2 containing the model complexity for the offsprings. A value NA is returned if an offspring is different (which is usually the case) from the two parents.

Author(s)

Francisco Javier Martinez de Pison. [e-mail]. EDMANS Group. https://edmans.webs.com/

See Also

ga_parsimony

jpison/GAparsimony documentation built on April 18, 2023, 8:34 p.m.