AbstractWe present a new hybrid method for solving constrained numerical and engineering optimization problems in this paper. The proposed hybrid method takes advantage of the differential evolution (DE) ability to find global optimum in problems with complex design spaces while directly enforcing feasibility of constraints using a modified augmented Lagrangian multiplier method. The basic steps of the proposed method are comprised of an outer iteration, in which the Lagrangian multipliers and various penalty parameters are updated using a first-order update scheme, and an inner iteration, in which a nonlinear optimization of the modified augmented Lagrangian function with simple bound constraints is implemented by a modified differential e...
In this paper, a novel sharp Augmented Lagrangian-based global optimization method is developed for ...
AbstractA novel modified differential evolution algorithm (NMDE) is proposed to solve constrained op...
A wide range of process systems engineering problems involve an optimisation formulation that is dif...
AbstractWe present a new hybrid method for solving constrained numerical and engineering optimizatio...
We consider the task of design optimization, where the constraint is a state equation that can only ...
In constrained optimisation, the augmented Lagrangian method is considered as one of the most effect...
Abstract. Nonlinear optimization problems introduce the possibility of multiple local optima. The ta...
Differential evolution (DE) algorithm has been shown to be a simple and efficient evolutionary algor...
Constrained Optimal Control Problems are notoriously difficult to solve accurately. Preliminary inve...
International audienceTrajectory optimization is an efficient approach for solving optimal control p...
The Interior Epigraph Directions (IED) method for solving constrained nonsmooth and nonconvex optimi...
International audienceWe consider the task of design optimization, where the constraint is a state e...
Differential Evolution is a simple and efficient stochastic, population-based heuristics for global ...
This paper presents a numerical study of two augmented Lagrangian algorithms to solve continuous con...
Nonlinear optimization problems introduce the possibility of multiple local optima. The task of glo...
In this paper, a novel sharp Augmented Lagrangian-based global optimization method is developed for ...
AbstractA novel modified differential evolution algorithm (NMDE) is proposed to solve constrained op...
A wide range of process systems engineering problems involve an optimisation formulation that is dif...
AbstractWe present a new hybrid method for solving constrained numerical and engineering optimizatio...
We consider the task of design optimization, where the constraint is a state equation that can only ...
In constrained optimisation, the augmented Lagrangian method is considered as one of the most effect...
Abstract. Nonlinear optimization problems introduce the possibility of multiple local optima. The ta...
Differential evolution (DE) algorithm has been shown to be a simple and efficient evolutionary algor...
Constrained Optimal Control Problems are notoriously difficult to solve accurately. Preliminary inve...
International audienceTrajectory optimization is an efficient approach for solving optimal control p...
The Interior Epigraph Directions (IED) method for solving constrained nonsmooth and nonconvex optimi...
International audienceWe consider the task of design optimization, where the constraint is a state e...
Differential Evolution is a simple and efficient stochastic, population-based heuristics for global ...
This paper presents a numerical study of two augmented Lagrangian algorithms to solve continuous con...
Nonlinear optimization problems introduce the possibility of multiple local optima. The task of glo...
In this paper, a novel sharp Augmented Lagrangian-based global optimization method is developed for ...
AbstractA novel modified differential evolution algorithm (NMDE) is proposed to solve constrained op...
A wide range of process systems engineering problems involve an optimisation formulation that is dif...