A Selection Process for Genetic Algorithm Using Clustering Analysis

A Selection Process for Genetic Algorithm Using Clustering Analysis

This article presents a newly proposed selection process for genetic algorithms on a class of unconstrained optimization problems. The k-means genetic algorithm selection process (KGA) is composed of four essential stages: clustering, membership phase, fitness scaling and selection. Inspired from th...

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Bibliographic Details
Main Authors: Adam Chehouri, Rafic Younes, Jihan Khoder, Jean Perron, Adrian Ilinca
Format: Article
Language:English
Published: MDPI AG 2017-11-01
Series:Algorithms
Subjects:
genetic algorithm
selection process
clustering
k-means
optimization algorithm
Online Access:https://www.mdpi.com/1999-4893/10/4/123

Internet

https://www.mdpi.com/1999-4893/10/4/123

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