Maintaining Healthy Population Diversity Using Adaptive Crossover, Mutation, and Selection

This paper presents ACROMUSE, a novel genetic algorithm (GA) which adapts crossover, mutation, and selection parameters. ACROMUSEs objective is to create and maintain a diverse population of highly-fit (healthy) individuals, capable of adapting quickly to fitness landscape change and well-suited to...

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Veröffentlicht in:IEEE transactions on evolutionary computation Jg. 15; H. 5; S. 692 - 714
Hauptverfasser: McGinley, Brian, Maher, John, O'Riordan, Colm, Morgan, Fearghal
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.10.2011
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Schlagworte:
Algorithm design and analysis
Algorithmics. Computability. Computer arithmetics
Applied sciences
Combinatorics
Combinatorics. Ordered structures
Computer science; control theory; systems
Convergence
Crossovers
Exact sciences and technology
Fitness
Genetic algorithm parameter adaptation
Genetic algorithms
Genetics
Graph theory
healthy population diversity
Information retrieval. Graph
Landscapes
Mathematical analysis
Mathematics
Mutation
Mutations
Operators
Optimization
Pressure measurement
Sciences and techniques of general use
Size measurement
Studies
Theoretical computing
Statistical analysis
Genetic algorithm
Multimodality
Evolutionary algorithm
Local optimum
Ecological niche
healthy population diversity
Graph theory
Adaptive method
Tournament
Fitness landscape
Genetic algorithm parameter adaptation
ISSN:1089-778X, 1941-0026
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Zusammenfassung:This paper presents ACROMUSE, a novel genetic algorithm (GA) which adapts crossover, mutation, and selection parameters. ACROMUSEs objective is to create and maintain a diverse population of highly-fit (healthy) individuals, capable of adapting quickly to fitness landscape change and well-suited to the efficient optimization of multimodal fitness landscapes. A new methodology is introduced for determining standard population diversity (SPD) and an original measure of healthy population diversity (HPD) is proposed. The SPD measure is employed to adapt crossover and mutation, while selection pressure is controlled by adapting tournament size according to HPD. In addition to selection pressure control, ACROMUSE tournament selection selects individuals according to healthy diversity contribution rather than fitness. This proposed selection mechanism simultaneously promotes diversity and fitness within the population. The performance of ACROMUSE is evaluated using various multimodal benchmark functions. Statistically significant results are presented comparing ACROMUSEs fitness and diversity performance to that of several other GAs. By maintaining a diverse population of healthy individuals, ACROMUSE responds to fitness landscape change by restoring better fitness scores faster than other GAs. Analysis of the adaptive operators illustrates that the key benefit of ACROMUSE is the synergy of the operators working together to achieve an effective balance between exploration and exploitation.
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ISSN:1089-778X
1941-0026
DOI:10.1109/TEVC.2010.2046173