DocumentCode :
296216
Title :
Efficient genetic programming based on binary decision diagrams
Author :
Yanagiya, Masayuki
Volume :
1
fYear :
1995
fDate :
Nov. 29 1995-Dec. 1 1995
Firstpage :
234
Abstract :
The performance of genetic programming can be dramatically improved by using a data structure coded by binary decision diagrams (BDDs). BDDs are a compact representation of Boolean functions using directed acyclic graphs. Efficient BDD-based crossover, mutation, and evaluation algorithms have been developed that allow all genetic operations to be performed on BDDs throughout the search. BDD-based GP reduces storage requirements by sharing isomorphic sub-graphs among individuals, and saves computational power by using a hash-based cache to make calculation more efficient. The proposed approach is powerful enough to solve the 20-multiplexer problem, which has never been reportedly achieved before
Keywords :
Binary decision diagrams; Boolean functions; Data structures; Decision trees; Genetic mutations; Genetic programming; Input variables; Laboratories; Large-scale systems; Performance evaluation;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Evolutionary Computation, 1995., IEEE International Conference on
Conference_Location :
Perth, WA, Australia
Print_ISBN :
0-7803-2759-4
Type :
conf
DOI :
10.1109/ICEC.1995.489151
Filename :
489151
Link To Document :
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