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International Conference on Numerical Computations: Theory and Algorithms

NUMTA 2019: Numerical Computations: Theory and Algorithms pp 17–31Cite as

Stability Analysis of DESA Optimization Algorithm

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11974))

Abstract

This paper investigates the dynamics of the hybrid evolutionary optimization algorithm, Differential Evolution-Simulated Annealing (DESA) algorithm with the binomial crossover and SA-like selection operators. A detailed mathematical framework of the operators of the DESA/rand/1/bin algorithm is provided to characterize the behavior of the DESA-population system. In DESA, the SA-like selection operation provides a nonzero probability of accepting a deteriorated solution that decreases with a sufficient number of generations. This paper shows that the system defined by the DESA-population is stable. Moreover, the DESA-population system time constant, learning and momentum rates are dependent on the value of the crossover constant and the probability of accepting deterioration in the quality of the objective function.

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Acknowledgements

The author RCA would like to thank the University of the Philippines Baguio, Baguio City, Philippines through the Ph.D. Incentive Grant and Research Dissemination Grant.

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Authors and Affiliations

  1. University of the Philippines Baguio, Baguio, Philippines

    Rizavel C. Addawe

  2. University of the Philippines School of Statistics, Diliman, Quezon City, Philippines

    Joselito C. Magadia

Authors
  1. Rizavel C. Addawe
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  2. Joselito C. Magadia
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Correspondence to Rizavel C. Addawe .

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Editors and Affiliations

  1. University of Calabria, Rende, Italy

    Yaroslav D. Sergeyev

  2. University of Calabria, Rende, Italy

    Dmitri E. Kvasov

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Addawe, R.C., Magadia, J.C. (2020). Stability Analysis of DESA Optimization Algorithm. In: Sergeyev, Y., Kvasov, D. (eds) Numerical Computations: Theory and Algorithms. NUMTA 2019. Lecture Notes in Computer Science(), vol 11974. Springer, Cham. https://doi.org/10.1007/978-3-030-40616-5_2

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  • DOI: https://doi.org/10.1007/978-3-030-40616-5_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-40615-8

  • Online ISBN: 978-3-030-40616-5

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