Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
4640445 | Journal of Computational and Applied Mathematics | 2011 | 10 Pages |
Abstract
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.
Related Topics
Physical Sciences and Engineering
Mathematics
Applied Mathematics
Authors
Ana Maria A.C. Rocha, Tiago F.M.C. Martins, Edite M.G.P. Fernandes,