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Empirical study of the improved UNIRANDI local search method

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Abstract

UNIRANDI is a stochastic local search algorithm that performs line searches from starting points along good random directions. In this paper, we focus on a modified version of this method. The new algorithm, addition to the random directions, considers more promising directions in order to speed up the optimization process. The performance of the new method is tested empirically on standard test functions in terms of function evaluations, success rates, error values, and CPU time. It is also compared to the previous version as well as other local search methods. Numerical results show that the new method is promising in terms of robustness and efficiency.

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Acknowledgements

This work was supported by the Sapientia Foundation - Institute for Scientific Research with the Grant No. 252/11/28/04/2015.

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Authors and Affiliations

  1. Faculty of Economics, Socio-Human Sciences and Engineering, Sapientia - Hungarian University of Transylvania, 530104, Miercurea Ciuc, Romania

    László Pál

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  1. László Pál
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Correspondence to László Pál.

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Pál, L. Empirical study of the improved UNIRANDI local search method. Cent Eur J Oper Res 25, 929–952 (2017). https://doi.org/10.1007/s10100-017-0470-2

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