Journal
JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS
Volume 235, Issue 16, Pages 4611-4620Publisher
ELSEVIER
DOI: 10.1016/j.cam.2010.04.020
Keywords
Augmented Lagrangian function; Artificial fish swarm; Stochastic convergence
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This paper presents an augmented Lagrangian methodology with a stochastic population based algorithm for solving nonlinear constrained global optimization problems. The method approximately solves a sequence of simple bound global optimization subproblems using a fish swarm intelligent algorithm. A stochastic convergence analysis of the fish swarm iterative process is included. Numerical results with a benchmark set of problems are shown, including a comparison with other stochastic-type algorithms. (C) 2010 Elsevier B.V. All rights reserved.
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