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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Veröffentlicht in:IEEE transactions on evolutionary computation Jg. 12; H. 2; S. 203 - 219
Hauptverfasser: Mininno, E., Cupertino, F., Naso, D.
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.04.2008
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Applied sciences
Artificial intelligence
Compact genetic algorithms (cGAs)
Computational efficiency
Computational modeling
Computer science; control theory; systems
Computer simulation
Design optimization
electric drives
Embedded system
embedded systems
Encoding
Evolutionary
Evolutionary algorithms
Exact sciences and technology
Field programmable gate arrays
Genetic algorithms
Learning and adaptive systems
Mathematical analysis
Mathematical models
Microcontrollers
online optimization
Optimization methods
Search methods
electric drives
Compact genetic algorithms (cGAs)
online optimization
embedded systems
Probabilistic approach
Microcontroller
Evolutionary algorithm
Updating
Electric drive
Optimization
Search algorithm
Boarded computer
Vector processing
Genetic algorithm
Experimental design
Assembler
Electric motor
ISSN:1089-778X, 1941-0026
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Zusammenfassung: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