Add to ORKGThis paper presents an augmented Lagrangian methodology with a stochastic population based algorithm for solving nonlinear constrained global optimiza-tion 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
This study presents a new two-swarm cooperative fish intelligence algorithm for solving the bound con...
Distribution based artificial fish swarm (DbAFS) is a new heuristic for continuous global optimizati...
This paper presents a numerical study of two augmented Lagrangian algorithms to solve continuous con...
AbstractThis paper presents an augmented Lagrangian methodology with a stochastic population based a...
Abstract. The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutatio...
This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed converg...
Abstract. An artificial fish swarm algorithm based on a filter methodo-logy for trial solutions acce...
The algorithm herein presented is a modified version of the artificial fish swarm algorithm for glob...
This chapter aims to address the challenging and demanding issue of solving a continuous nonlinear c...
This paper presents a numerical study of a stochastic augmented Lagrangian algorithm to solve contin...
Ana Maria A.C. Rocha, M. Fernanda P. Costa and Edite M.G.P. Fernandes, An Artificial Fish Swarm Filt...
A fish swarm intelligence algorithm based on the filter set concept to accept, at each iteration, a ...
Abstract This study presents a new two-swarm cooperative fish intelligence algorithm for solving the...
The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutation operator...
Nonlinear programming problems are known to be difficult to solve, especially those that involve a m...
This study presents a new two-swarm cooperative fish intelligence algorithm for solving the bound con...
Distribution based artificial fish swarm (DbAFS) is a new heuristic for continuous global optimizati...
This paper presents a numerical study of two augmented Lagrangian algorithms to solve continuous con...
AbstractThis paper presents an augmented Lagrangian methodology with a stochastic population based a...
Abstract. The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutatio...
This paper aims to present a hyperbolic augmented Lagrangian (HAL) framework with guaranteed converg...
Abstract. An artificial fish swarm algorithm based on a filter methodo-logy for trial solutions acce...
The algorithm herein presented is a modified version of the artificial fish swarm algorithm for glob...
This chapter aims to address the challenging and demanding issue of solving a continuous nonlinear c...
This paper presents a numerical study of a stochastic augmented Lagrangian algorithm to solve contin...
Ana Maria A.C. Rocha, M. Fernanda P. Costa and Edite M.G.P. Fernandes, An Artificial Fish Swarm Filt...
A fish swarm intelligence algorithm based on the filter set concept to accept, at each iteration, a ...
Abstract This study presents a new two-swarm cooperative fish intelligence algorithm for solving the...
The herein presented mutation-based artificial fish swarm (AFS) algorithm includes mutation operator...
Nonlinear programming problems are known to be difficult to solve, especially those that involve a m...
This study presents a new two-swarm cooperative fish intelligence algorithm for solving the bound con...
Distribution based artificial fish swarm (DbAFS) is a new heuristic for continuous global optimizati...
This paper presents a numerical study of two augmented Lagrangian algorithms to solve continuous con...