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hLCGA: A Hybrid Competitive Coevolutionary Genetic Algorithm
Author(s) -
Gregoire Danoy,
Pascal Bouvry,
Tomy Martins
Publication year - 2006
Publication title -
2006 sixth international conference on hybrid intelligent systems (his'06)
Language(s) - English
Resource type - Book series
ISBN - 0-7695-2662-4
DOI - 10.1109/his.2006.32
We introduce in this article a new hybrid coevolutionary algorithm called hLCGA (hybrid Loosely Coupled Genetic Algorithm) that consists in combining a competitive coevolutionary genetic algorithm and a local search algorithm. We apply it to the Rosenbrock function optimization problem and compare the results of five hybrid variants to the original LCGA. We show the advantages of hybridizing a coevolutionary algorithm with local search algorithms in terms of solution quality and convergence speed.

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