Crossover versus Mutation: A Comparative Analysis of the Evolutionary Strategy of Genetic Algorithms Applied to Combinatorial Optimization Problems
Since their first formulation, genetic algorithms (GAs) have been one of the most widely used techniques to solve combinatorial optimization problems. The basic structure of the GAs is known by the scientific community, and thanks to their easy application and good performance, GAs are the focus of...
Saved in:
Main Authors: | E. Osaba, R. Carballedo, F. Diaz, E. Onieva, I. de la Iglesia, A. Perallos |
---|---|
Format: | Article |
Language: | English |
Published: |
Wiley
2014-01-01
|
Series: | The Scientific World Journal |
Online Access: | http://dx.doi.org/10.1155/2014/154676 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Similar Items
-
An Improved Directed Crossover Genetic Algorithm Based on Multilayer Mutation
by: Feng Xie, et al.
Published: (2022-01-01) -
Fuzzy logic applied to tunning mutation size in evolutionary algorithms
by: Krzysztof Pytel
Published: (2025-01-01) -
An Improved Strategy for Genetic Evolutionary Structural Optimization
by: Nannan Cui, et al.
Published: (2020-01-01) -
A combinatorial commutativity property for rings
by: Howard E. Bell, et al.
Published: (2002-01-01) -
The combinatorial structure of trigonometry
by: Adel F. Antippa
Published: (2003-01-01)