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.
Rocha et al. reported an augmented Lagrangian methodology with a stochastic population based algorithm, which solves a sequence of simple bound global optimization subproblems using a fish swarm intelligent algorithm REF .
An augmented Lagrangian fish swarm based method for global optimization
J. Comput. Appl. Math.
J. Comput. Appl. Math.
Mathematics Computer Science