Improved Genetic Algorithm based on Search Parameters Dynamically Adjust and its Application

DOI

10.2991/emeit.2012.522How to use a DOI?

Keywords

genetic algorithms, real coding, premature convergence

Abstract

Practical application of genetic algorithm is easy to premature convergence and accuracy of search results is not high. Optimal value for the premature convergence and low accuracy to dynamically adjust the search parameters to optimize the calculation, the whole process of evolution, the algorithm always maintain a strong global search ability and local search capabilities, test results show that genetic such improved algorithm is effective, easy to fall into local optimum, and can greatly improve the accuracy of the optimal solution..

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/).

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TY  - CONF
AU  - Yongsheng Jia
AU  - Xiujian Lv
PY  - 2012/09
DA  - 2012/09
TI  - Improved Genetic Algorithm based on Search Parameters Dynamically Adjust and its Application
BT  - Proceedings of the 2nd International Conference on Electronic & Mechanical Engineering and Information Technology (EMEIT 2012)
PB  - Atlantis Press
SP  - 2349
EP  - 2352
SN  - 1951-6851
UR  - https://doi.org/10.2991/emeit.2012.522
DO  - 10.2991/emeit.2012.522
ID  - Jia2012/09
ER  -