Fundamental Research on Genetic Algorithms

DOI

10.2991/iccasm.2012.289How to use a DOI?

Keywords

Genetic Algorithms, Implicit Parallelism, Global Searching, Robustness

Abstract

Genetic Algorithms uses the population selection technology, newer population is generated from current population by cross, mutation and other genetic operations, and gradually make the population to evolve the optimization result. Compared with traditional optimization methods, Genetic Algorithm has two notable characters, one is the latent parallelism and the other is searching in the whole area. And because of its independence, global optimization and implicit parallelism, GA is developed and applied by more and more people, so has been widely used in many fields, such as adaptive control, combinatorial optimization, pattern recognition, machine learning, artificial life and management decisions,etc.

Copyright

© 2012, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

Download article (PDF)

TY  - CONF
AU  - Chang Zhou
PY  - 2012/08
DA  - 2012/08
TI  - Fundamental Research on Genetic Algorithms
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 1135
EP  - 1138
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.289
DO  - 10.2991/iccasm.2012.289
ID  - Zhou2012/08
ER  -