Table of Content

Open Access iconOpen Access

ARTICLE

A Hybrid GABC-GA Algorithm for Mechanical Design Optimization Problems

Hui Zhi1,2, Sanyang Liu1

1 School of Mathematics and Statistics, Xidian University, 710126, Xian, China
2 School of Huaqing and Xi-an University of Architecture and Technology, 710055, Xian, China

* Corresponding Authors: Hui Zhi, email, email

Intelligent Automation & Soft Computing 2019, 25(4), 815-825. https://doi.org/10.31209/2019.100000085

Abstract

In this paper, we proposed a hybrid algorithm, which is embedding the genetic operators in the global-best-guided artificial bee colony algorithms called GABCGA to solve the nonlinear design optimization problems. The genetic algorithm has no memory function and good at find global optimization with large probability, but the artificial bee colony algorithm not have selection, crossover and mutation operator and most significant at local search. The hybrid algorithm balances the exploration and exploitation ability further by combining the advantages of both. The experimental results of five engineering optimization and comparisons with existing approaches show that the proposed approach is outperforms to those typical approaches in terms of the quality of the results solutions in most cases.

Keywords


Cite This Article

APA Style
Zhi, H., Liu, S. (2019). A hybrid GABC-GA algorithm for mechanical design optimization problems. Intelligent Automation & Soft Computing, 25(4), 815-825. https://doi.org/10.31209/2019.100000085
Vancouver Style
Zhi H, Liu S. A hybrid GABC-GA algorithm for mechanical design optimization problems. Intell Automat Soft Comput . 2019;25(4):815-825 https://doi.org/10.31209/2019.100000085
IEEE Style
H. Zhi and S. Liu, "A Hybrid GABC-GA Algorithm for Mechanical Design Optimization Problems," Intell. Automat. Soft Comput. , vol. 25, no. 4, pp. 815-825. 2019. https://doi.org/10.31209/2019.100000085



cc This work is licensed under a Creative Commons Attribution 4.0 International License , which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
  • 1420

    View

  • 1150

    Download

  • 0

    Like

Share Link