Title

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.

Identifier

DOI: http://dx.doi.org/10.1109/ICSEng.2008.71

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