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Smoothing approximation to the lower order exact penalty function for inequality constrained optimization.

Shujun LianNana Niu
Published in: Journal of inequalities and applications (2018)
For inequality constrained optimization problem, we first propose a new smoothing method to the lower order exact penalty function, and then show that an approximate global solution of the original problem can be obtained by solving a global solution of a smooth lower order exact penalty problem. We propose an algorithm based on the smoothed lower order exact penalty function. The global convergence of the algorithm is proved under some mild conditions. Some numerical experiments show the efficiency of the proposed method.
Keyphrases
  • density functional theory
  • machine learning
  • deep learning
  • molecular dynamics
  • neural network