The Linkage Tree Genetic Algorithm

@inproceedings{Thierens2010TheLT,
  title={The Linkage Tree Genetic Algorithm},
  author={D. Thierens},
  booktitle={PPSN},
  year={2010}
}
  • D. Thierens
  • Published in PPSN 2010
  • Mathematics, Computer Science
  • We introduce the Linkage Tree Genetic Algorithm (LTGA), a competent genetic algorithm that learns the linkage between the problem variables. The LTGA builds each generation a linkage tree using a hierarchical clustering algorithm. To generate new offspring solutions, the LTGA selects two parent solutions and traverses the linkage tree starting from the root. At each branching point, the parent pair is recombined using a crossover mask defined by the clustering at that particular tree node. The… CONTINUE READING
    61 Citations
    Learning the Neighborhood with the Linkage Tree Genetic Algorithm
    Predetermined versus learned linkage models
    • 8
    • PDF
    Linkage tree genetic algorithms: variants and analysis
    • 16
    • Highly Influenced
    • PDF
    Linkage neighbors, optimal mixing and forced improvements in genetic algorithms
    • 27
    • PDF
    On the usefulness of linkage processing for solving MAX-SAT
    • 14
    • PDF
    Hierarchical problem solving with the linkage tree genetic algorithm
    • 43
    • PDF
    Cooperative coevolutionary genetic algorithm using hierarchical clustering of linkage tree
    On Measures to Build Linkage Trees in LTGA
    • 8
    • PDF

    References

    SHOWING 1-10 OF 16 REFERENCES
    CrossNet: a framework for crossover with network-based chromosomal representations
    • 11
    • PDF
    Network crossover performance on NK landscapes and deceptive problems
    • 11
    • PDF
    Linkage in Evolutionary Computation
    • 19
    The Design of Innovation: Lessons from and for Competent Genetic Algorithms
    • 1,014
    Performance of evolutionary algorithms on NK landscapes with nearest neighbor interactions and tunable overlap
    • 38
    • PDF
    A new method for linkage learning in the ECGA
    • 8
    Performance of Evolutionary Algorithms on Random Decomposable Problems
    • 15
    • PDF
    Hierarchical Clustering Using Mutual Information
    • 196
    • PDF