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GAAP. genetic algorithm with auxiliary populations applied to continuous optimization problems

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3 Author(s)
Corbalan, L. ; III-LIDI (Inst. of Res. in Comput. Sci. LIDI), Nat. Univ. of La Plata, Buenos Aires, Argentina ; Hasperue, W. ; Lanzarini, L.

Genetic algorithms have been used successfully to solve continuous optimization problems. However, an early convergence to low-quality solutions is one of the most common difficulties encountered when using these strategies. In this paper, a method that combines multiple auxiliary populations with the main population of the algorithm is proposed. The role of the auxiliary populations is dual: to prevent or hinder the early convergence to local suboptimal solutions, and to provide a local search mechanism for a greater exploitation of the most promising regions within the search space.

Published in:

Information Technology Interfaces (ITI), Proceedings of the ITI 2012 34th International Conference on

Date of Conference:

25-28 June 2012

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