Empirical study of the improved UNIRANDI local search method

László Pál ()
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László Pál: Sapientia - Hungarian University of Transylvania

Central European Journal of Operations Research, 2017, vol. 25, issue 4, No 11, 929-952

Abstract: 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.

Keywords: Direct search; Local search; Global optimization; Benchmarking (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (1)

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DOI: 10.1007/s10100-017-0470-2

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