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A novel genetic algorithm with orthogonal prediction for global numerical optimization
- Authors
- Zhang, Jun; Zhong, Jing-Hui; Hu, Xiao-Min
- Issue Date
- Dec-2008
- Publisher
- Springer Verlag
- Keywords
- Evolutionary algorithm; Genetic algorithm; Local search; Numerical optimization; Orthogonal design method
- Citation
- Simulated Evolution and Learning 7th International Conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008, Proceedings, v.5361, pp 31 - 40
- Pages
- 10
- Indexed
- SCI
SCOPUS
- Journal Title
- Simulated Evolution and Learning 7th International Conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008, Proceedings
- Volume
- 5361
- Start Page
- 31
- End Page
- 40
- Abstract
- This paper proposes a novel orthogonal predictive local search (OPLS) to enhance the performance of the conventional genetic algorithms. OPLS operation predicts the most promising direction for the individuals to explore their neighborhood. It uses the orthogonal design method to sample orthogonal combinations to make the prediction. The resulting algorithm is termed the orthogonal predictive genetic algorithm (OPGA). OPGA has been tested on eleven numerical optimization functions in comparison with some typical algorithms. The results demonstrate the effectiveness of the proposed algorithm for achieving better solutions with a faster convergence speed. © 2008 Springer Berlin Heidelberg.
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Related Researcher
- ZHANG, Jun
- ERICA 공학대학 (SCHOOL OF ELECTRICAL ENGINEERING)