Abstract
By using the feedback of genetic informatione, a rational genetic algorithm (RGA) is proposed to overcome the drawbacks of conventional genetic algorithms such as slow convergence. The genetic information (GI) is extended in order to improve its completeness, and the rational genetic operators are rebuilt with more generality based on the extended GI. A more general specification for the whole RGA is given and the global convergence of the RGA is shown. Theoretical analysis and practical application to motion planning are given to illustrate the effectiveness of RGA.
Original language | English |
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Pages (from-to) | 1017-1021 |
Number of pages | 5 |
Journal | Kongzhi yu Juece/Control and Decision |
Volume | 19 |
Issue number | 9 |
Publication status | Published - 1 Sept 2004 |
Externally published | Yes |
Keywords
- Genetic information
- Motion planning
- Rational genetic algorithm (RGA)
ASJC Scopus subject areas
- Control and Systems Engineering
- Software
- Control and Optimization
- Artificial Intelligence