Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
A computational view of population genetics
Random Structures & Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
The Design of Innovation: Lessons from and for Competent Genetic Algorithms
Convergence Models of Genetic Algorithm Selection Schemes
PPSN III Proceedings of the International Conference on Evolutionary Computation. The Third Conference on Parallel Problem Solving from Nature: Parallel Problem Solving from Nature
A crossover for complex building blocks overlapping
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Linkage identification by fitness difference clustering
Evolutionary Computation
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
Effective linkage learning using low-order statistics and clustering
IEEE Transactions on Evolutionary Computation - Special issue on evolutionary algorithms based on probabilistic models
Spurious dependencies and EDA scalability
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Graph clustering based model building
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Influence of selection on structure learning in markov network EDAs: an empirical study
Proceedings of the 14th annual conference 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
A niching scheme for EDAs to reduce spurious dependencies
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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This paper aims at an important, but poorly studied area in genetic algorithm (GA) field: How to design the crossover operator for problems with overlapping building blocks (BBs). To investigate this issue systematically, the relationship between an inaccurate linkage model and the convergence time of GA is studied. Specifically, the effect of the error of so-called false linkage is analogized to a lower exchange probability of uniform crossover. The derived qualitative convergence-time model is used to develop a scalable recombination strategy for problems with overlapping BBs. A set of problems with circularly overlapping BBs exemplify the recombination strategy.