A global optimization method based on the reduced simplicial statistical model

    Antanas Žilinskas Info
    Julius Žilinskas Info
DOI: https://doi.org/10.3846/13926292.2011.602988

Abstract

A simplicial statistical model of multimodal functions is used to construct a global optimization algorithm. The search for the global minimum in the multidimensional space is reduced to the search over the edges of simplices covering the feasible region combined with the refinement of the cover. The refinement is performed by subdivision of selected simplices taking into account the point where the objective function value has been computed at the current iteration. For the search over the edges the one-dimensional P-algorithm based on the statistical smooth function model is adapted. Differently from the recently proposed algorithm here the statistical model is used for modelling the behaviour of the objective function not over the whole simplex but only over its edges. Testing results of the proposed algorithm are included.

Keywords:

global optimization, statistical models, simplicial partition

How to Cite

Žilinskas, A., & Žilinskas, J. (2011). A global optimization method based on the reduced simplicial statistical model. Mathematical Modelling and Analysis, 16(3), 451-460. https://doi.org/10.3846/13926292.2011.602988

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August 24, 2011
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2011-08-24

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How to Cite

Žilinskas, A., & Žilinskas, J. (2011). A global optimization method based on the reduced simplicial statistical model. Mathematical Modelling and Analysis, 16(3), 451-460. https://doi.org/10.3846/13926292.2011.602988

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