Real-Valued Compact Genetic Algorithms for Embedded Microcontroller Optimization

Recent research on compact genetic algorithms (cGAs) has proposed a number of evolutionary search methods with reduced memory requirements. In cGAs, the evolution of populations is emulated by processing a probability vector with specific update rules. This paper considers the implementation of cGAs...

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Bibliographic Details
Published in:IEEE transactions on evolutionary computation Vol. 12; no. 2; pp. 203 - 219
Main Authors: Mininno, E., Cupertino, F., Naso, D.
Format: Journal Article
Language:English
Published: New York, NY IEEE 01.04.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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ISSN:1089-778X, 1941-0026
Online Access:Get full text
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Summary:Recent research on compact genetic algorithms (cGAs) has proposed a number of evolutionary search methods with reduced memory requirements. In cGAs, the evolution of populations is emulated by processing a probability vector with specific update rules. This paper considers the implementation of cGAs in microcontroller-based control platforms. In particular, to overcome some problems related to the binary encoding schemes adopted in most cGAs, this paper also proposes a new variant based on a real-valued solution coding. The presented variant achieves final solutions of the same quality as those found by binary cGAs, with a significantly reduced computational cost. The potential of the proposed approach is assessed by means of an extensive comparative study, which includes numerical results on benchmark functions, simulated and experimental microcontroller design problems.
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ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2007.896689