Adaptation in natural and artificial systems
Adaptation in natural and artificial systems
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
A New Class of the Crossover Operators for the Numerical Optimization
Proceedings of the 6th International Conference on Genetic Algorithms
Toward More Powerful Recombinations
Proceedings of the 6th International Conference on Genetic Algorithms
A survey on chromosomal structures and operators for exploiting topological linkages of genes
GECCO'03 Proceedings of the 2003 international conference on Genetic and evolutionary computation: PartII
An empirical study on the synergy of multiple crossover operators
IEEE Transactions on Evolutionary Computation
More effective crossover operators for the all-pairs shortest path problem
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part I
Meaningful representation and recombination of variable length genomes
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
More effective crossover operators for the all-pairs shortest path problem
Theoretical Computer Science
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Spatial based gene selection for division of chromosomes used by crossover operators is proposed for three-dimensional problems. This spatial selection is shown to preserve more genetic material and reduce the disruptive effects of crossover. The disruptive effects of crossover can be quantified by counting the destruction of subgraphs that represent strong linkages between genes. The spatial operator is compared to simple crossover on a practical class of molecular clustering searches. This comparison shows that the spatial crossover significantly out performs simple crossover. Consistent good performance for spatial crossover is demonstrated on the molecular cluster conformation problem [9].