Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Finding Multimodal Solutions Using Restricted Tournament Selection
Proceedings of the 6th International Conference on Genetic Algorithms
Linkage learning, overlapping building blocks, and systematic strategy for scalable recombination
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Gene Expression and Fast Construction of Distributed Evolutionary Representation
Evolutionary Computation
Efficient linkage discovery by limited probing
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Empirical investigations on parallel competent genetic algorithms
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Dependency structure matrix, genetic algorithms, and effective recombination
Evolutionary Computation
Research frontier: linkage discovery through data mining
IEEE Computational Intelligence Magazine
Proceedings of the 13th annual conference on Genetic and evolutionary computation
A test function with full controllability over overlapping: estimation of distribution algorithms
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
A test problem with adjustable degrees of overlap and conflict among subproblems
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Design of test problems for discrete estimation of distribution algorithms
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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We propose a crossover method to combine complexly overlapping building blocks (BBs). Although there have been several techniques to identify linkage sets of loci o form a BB [4, 6, 7, 10, 11], the way to to realize effective crossover from the linkage information from such techniques has not been studied enough. Especially for problems with overlapping BBs, a crossover method proposed by Yu et al. [13] is the first and only known research, however it cannot perform well for problems with complexly overlapping BBs due to insufficient variety of crossover sites. In this paper, we propose a crossover method which examines values of given parental strings minutely and defines which variables are exchanged to produce new and different strings without increasing BB disruptions as much as possible. The method is combined with a scalable linkage identification technique to construct an efficient algorithm for problems with overlapping BBs. We design test functions with controllable complexity of overlap and test the method with the functions.