An Improved Quantum Evolution Algorithm and Performance Analysis

DOI

10.2991/iccasm.2012.159How to use a DOI?

Keywords

Multiple quantum computation, quantum-inspired evolutionary algorithm, genetic optimization, estimation of distribution

Abstract

To tackle the shortcoming of deficient using of feedback information in quantum-inspired evolutionary computing and catastrophe such as quantum mutation, the improved quantum-inspired evolutionary algorithm (IQEA ) is proposed. The crossover and mutation operators of genetic algorithm are introduced to the quantum evolution algorithm, at the same time, the better individuals information is applied to the generation of the population applying the probability evaluation model of the estimation of distribution algorithm. Theory analyze and test function simulation experiments show that the improved quantum genetic algorithm is characterized by rapid convergence , excellent robustness and so on.

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  - Yi Zhang
AU  - Xiuxia Yang
AU  - Shaolei Zhou
PY  - 2012/08
DA  - 2012/08
TI  - An Improved Quantum Evolution Algorithm and Performance Analysis
BT  - Proceedings of the 2012 International Conference on Computer Application and System Modeling (ICCASM 2012)
PB  - Atlantis Press
SP  - 627
EP  - 629
SN  - 1951-6851
UR  - https://doi.org/10.2991/iccasm.2012.159
DO  - 10.2991/iccasm.2012.159
ID  - Zhang2012/08
ER  -