An artificial fish swarm algorithm based hyperbolic augmented Lagrangian method

By Costa, M.F.P.; Rocha, A.M.A.C.; Fernandes, E.M.G.P.

Journal of Computational and Applied Mathematics

2014

Abstract

This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed convergence to an ϵ-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 ϵk-global minimizer of the HAL function is guaranteed with probability one, where ϵk→ϵ as k→∞. Preliminary numerical experiments show that the proposed paradigm compares favorably with other penalty-type methods.

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