A Hybrid Orthogonal Genetic Algorithm for Global numerical Optimization
Document Type
Conference Proceeding
Publication Date
2008
Publication Title
in 19th International Conference on Systems Engineering, 2008. ICSENG '08
Publisher
IEEE
First page number:
282
Last page number:
287
Abstract
In this paper, a hybrid orthogonal genetic algorithm (HOGA) is presented to solve global numerical optimization problems of continuous variables. Based on traditional genetic algorithms, the HOGA has been augmented with a robust selection operator and an intelligent crossover operator. These augmentations reduce statistical bias while improving convergence times and relative accuracy of the solutions. Examples show that HOGA can effectively solve a number of multimodal problems which are widely accepted as optimization benchmarks.
Keywords
Genetic algorithms
Disciplines
Controls and Control Theory | Electrical and Computer Engineering | Engineering | Signal Processing | Systems and Communications
Language
English
Permissions
Use Find in Your Library, contact the author, or interlibrary loan to garner a copy of the item. Publisher policy does not allow archiving the final published version. If a post-print (author's peer-reviewed manuscript) is allowed and available, or publisher policy changes, the item will be deposited.
Repository Citation
Stubberud, P.,
Jackson, M. E.
(2008).
A Hybrid Orthogonal Genetic Algorithm for Global numerical Optimization.
in 19th International Conference on Systems Engineering, 2008. ICSENG '08
282-287.
IEEE.