An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method

  • Authors:
  • M. Fernanda P. Costa;Ana Maria A. C. Rocha;Edite M. G. P. Fernandes

  • Affiliations:
  • -;-;-

  • Venue:
  • Journal of Computational and Applied Mathematics
  • Year:
  • 2014

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Abstract

This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed convergence to an @e-global minimizer of a constrained nonlinear optimization problem. The bound constrained subproblems that emerge at each iteration k of the framework are solved by an improved artificial fish swarm algorithm. Convergence to an @e^k-global minimizer of the HAL function is guaranteed with probability one, where @e^k-@e as k-~. Preliminary numerical experiments show that the proposed paradigm compares favorably with other penalty-type methods.