© 2015 Elsevier Inc. All rights reserved. Differential Search method is recently proposed to solve box constrained global optimization problems. In this paper, we will further extend this method to solve generalized constrained optimization problems, particularly for structure design optimization problems. To handle the constraints, we first propose a novel dynamic S-type soft-threshold penalty method. Then, the original constrained optimization problem is transformed into a sequence of unconstrained optimization problems. The proposed method is mainly comprised of two steps: parameter iteration and solution iteration. The parameter iteration is to update the dynamic penalty parameter through a soft-threshold scheme and the solution iterati...
In the past few decades, metaheuristic optimization methods have emerged as an effective approach fo...
This paper proposes an alternative approach to efficient solving of nonlinear constrained optimizati...
Bound-constrained optimization has wide applications in science and engineering. In the last two dec...
Differential search (DS) is a recently developed derivative-free global heuristic optimization algor...
Differential evolution (DE) is a population-based metaheuristic search algorithm that optimizes a pr...
This study proposes an optimization method called Global Best Algorithm for successful solution of c...
Engineering design optimization problems are formulated as large-scale mathematical programming prob...
This paper presents a population-based evolutionary computation model for solving continuous constra...
Abstract. Nonlinear optimization problems introduce the possibility of multiple local optima. The ta...
In the present paper, dynamic identification problem of a FE structure with unknown parameters is so...
The population-based evolutionary algorithms have emerged as powerful mechanism for finding optimum ...
The standard cuckoo search algorithm is of low accuracy and easy to fall into local optimal value in...
The population-based evolutionary algorithms have emerged as powerful mechanism for finding optimum ...
Many engineering optimization problems can be state as function optimization with constrained, intel...
A directed searching optimization algorithm (DSO) is proposed to solve constrained optimization prob...
In the past few decades, metaheuristic optimization methods have emerged as an effective approach fo...
This paper proposes an alternative approach to efficient solving of nonlinear constrained optimizati...
Bound-constrained optimization has wide applications in science and engineering. In the last two dec...
Differential search (DS) is a recently developed derivative-free global heuristic optimization algor...
Differential evolution (DE) is a population-based metaheuristic search algorithm that optimizes a pr...
This study proposes an optimization method called Global Best Algorithm for successful solution of c...
Engineering design optimization problems are formulated as large-scale mathematical programming prob...
This paper presents a population-based evolutionary computation model for solving continuous constra...
Abstract. Nonlinear optimization problems introduce the possibility of multiple local optima. The ta...
In the present paper, dynamic identification problem of a FE structure with unknown parameters is so...
The population-based evolutionary algorithms have emerged as powerful mechanism for finding optimum ...
The standard cuckoo search algorithm is of low accuracy and easy to fall into local optimal value in...
The population-based evolutionary algorithms have emerged as powerful mechanism for finding optimum ...
Many engineering optimization problems can be state as function optimization with constrained, intel...
A directed searching optimization algorithm (DSO) is proposed to solve constrained optimization prob...
In the past few decades, metaheuristic optimization methods have emerged as an effective approach fo...
This paper proposes an alternative approach to efficient solving of nonlinear constrained optimizati...
Bound-constrained optimization has wide applications in science and engineering. In the last two dec...