Scilab Website | Contribute with GitLab | Mailing list archives | ATOMS toolboxes
Scilab Online Help
5.3.2 - 日本語

Change language to:
English - Français - Português

Please note that the recommended version of Scilab is 2025.0.0. This page might be outdated.
See the recommended documentation of this function

Scilab help >> Genetic Algorithms > selection_ga_elitist

selection_ga_elitist

An 'elitist' selection function

Calling Sequence

[Pop_out,FObj_Pop_out,Efficiency,MO_Total_FObj_out] = selection_ga_elitist(Pop_in,Indiv1,Indiv2,FObj_Pop_in,FObj_Indiv1,FObj_Indiv2,MO_Total_FObj_in,MO_FObj_Indiv1,MO_FObj_Indiv2,param)

Arguments

Pop_in

The initial population of individuals.

Indiv1

a first set of childs generated via crossover + mutation.

Indiv2

a second set of childs generated via crossover + mutation.

FObj_Pop_in

a vector of objective function values associated to each individuals of Pop_in.

FObj_Indiv1

a vector of objective function values associated to each individuals of Indiv1.

FObj_Indiv2

a vector of objective function values associated to each individuals of Indiv2.

MO_Total_FObj_in

a matrix of multi-objective function values associated to each individuals of Pop_in.

MO_FObj_Indiv1

a matrix of multi-objective function values associated to each individuals of Indiv1.

MO_FObj_Indiv2

a matrix of multi-objective function values associated to each individuals of Indiv2.

param

a list of parameters. - 'pressure': the selection pressure coefficient. Each individuals with 0 efficiency will have an efficiency value equal to 'pressure'.

Pop_out

all the selected individuals in a population of size pop_size.

FObj_Pop_out

all the objective function values associated to each individuals of Pop_out.

Efficiency

all the efficiency values associated to each individuals of Pop_out.

MO_Total_FObj_out

all the multi-objective function values associated to each individuals of Pop_out.

Description

  • This function performs the elitist selection function. We select the best individuals in the set of parents and childs individuals.

See Also

Authors

Yann COLLETTE

ycollet@freesurf.fr

<< pareto_filter Genetic Algorithms selection_ga_random >>

Copyright (c) 2022-2024 (Dassault Systèmes)
Copyright (c) 2017-2022 (ESI Group)
Copyright (c) 2011-2017 (Scilab Enterprises)
Copyright (c) 1989-2012 (INRIA)
Copyright (c) 1989-2007 (ENPC)
with contributors
Last updated:
Thu May 12 11:45:56 CEST 2011