Efficient Linkage Discovery by Limited Probing
Evolutionary Computation
Convergence Time for the Linkage Learning Genetic Algorithm
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
A parallel genetic algorithm based on linkage identification
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartI
Research frontier: linkage discovery through data mining
IEEE Computational Intelligence Magazine
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Interaction detection for hybrid decomposable problems
Proceedings of the 13th annual conference on Genetic and evolutionary computation
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Genetic algorithms (GAs) process building blocks (BBs) mixed and tested through genetic recombination operators. To realize effective BB processing, linkage identification, which detects a set of tightly linked loci, is essential. This paper proposes linkage identification with epistasis measures (LIEM), which detects linkage groups based on a pair-wise epistasis measure.