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Intelligent Engineering Systems through Artificial Neural Networks, Volume 16

Editor
Cihan H. Dagli
Cihan H. Dagli
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Anna L. Buczak
Anna L. Buczak
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David L. Enke
David L. Enke
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Mark Embrechts
Mark Embrechts
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Okan Ersoy
Okan Ersoy
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ISBN-10:
0791802566
No. of Pages:
1000
Publisher:
ASME Press
Publication date:
2006

Understanding how variation operators work leads to a better understanding both of the search space and of the problem being solved. This study examines the behavior of mutation and crossover operators in genetic programming using parse trees to find solutions to 3-parity and 4-parity. The standard subtree crossover and subtree mutation operators are studied along with two new operators, fold mutation and fusion crossover. They are studied in terms of how often and how fast they solve the problem; how much they change the fitness on average; and what proportion of variations are neutral, harmful, and helpful. It is found that operators behave differently when used alone than when used together with another operator and that some operators behave differently when solving 3-parity and when solving 4-parity.

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