Research on Genetic Algorithm Solving Multi-modal Optimization Problem

DOI

10.2991/meici-15.2015.125How to use a DOI?

Keywords

Genetic algorithm; Multi-modal optimization problem; Fitness difference of local optima; Searching space scale; Chaos.

Abstract

It has become a widely concerned problem in genetic algorithm and even evolutionary computing field that how to apply genetic algorithm to solve multi-modal optimization problem, and it is the basis for genetic algorithm theory and practical application. Achievements in this aspect are emerging in endless, while theoretical researches are comparatively less. Especially there is no research on influences of external parameters to performances of applying genetic algorithm to solve multi-modal optimization problem yet. This article mainly carries out theoretical researches on this aspect and generalizes corresponding conclusions. The generalized theoretical results are used to improve searching performance of genetic algorithm in solving multi-modal optimization problem. Main research contents of this article include brief review of multi-modal optimization problem and genetic algorithm, analysis of research status of applying genetic algorithm to solve multi-model optimization problem, and introduction to basic theory and development trend of genetic algorithm. In this article, two kinds of complicated evolutionary systems based on infinite population model of genetic algorithm are analyzed, two kinds of new population evolutionary systems are built on this basis, and dynamic equation under the condition of single-gene is derived as well.

Copyright

© 2015, 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  - Shoubai Xiao
PY  - 2015/06
DA  - 2015/06
TI  - Research on Genetic Algorithm Solving Multi-modal Optimization Problem
BT  - Proceedings of the 2015 International Conference on Management, Education, Information and Control
PB  - Atlantis Press
SP  - 712
EP  - 718
SN  - 1951-6851
UR  - https://doi.org/10.2991/meici-15.2015.125
DO  - 10.2991/meici-15.2015.125
ID  - Xiao2015/06
ER  -