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Stability Analysis of DESA Optimization Algorithm

  • Rizavel C. AddaweEmail author
  • Joselito C. Magadia
Conference paper
  • 24 Downloads
Part of the Lecture Notes in Computer Science book series (LNCS, 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.

Keywords

Differential evolution - simulated annealing Stability analysis Lyapunov’s theorem 

Notes

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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Copyright information

© Springer Nature Switzerland AG 2020

Authors and Affiliations

  1. 1.University of the Philippines BaguioBaguioPhilippines
  2. 2.University of the Philippines School of StatisticsQuezon CityPhilippines

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