AbstractIn this paper, efficient simultaneous strategies are presented for the optimization of practical problems involving PDE-models. In particular, reduced sequential quadratic programming methods for problems with only few influence variables and simultaneous quadratic programming iterations are discussed. As a result we obtain algorithms whose overall computational complexity is reduced considerably in comparison to a black-box approach
The problem of determining whether quadratic programming models possess either unique or multiple op...
The problem of determining whether quadratic programming models possess either unique or multiple op...
Sequential approximate optimization (SAO) methods aimed at structural optimization often use recipro...
AbstractIn this paper, efficient simultaneous strategies are presented for the optimization of pract...
In this work, we consider the relevant class of Standard Quadratic Programming problems and we propo...
This book results from the authors work done on simulation based optimization problems at the Depart...
This book results from the authors work done on simulation based optimization problems at the Depart...
We describe a method for solving large-scale general quadratic programming problems. Our method is b...
Abstract: "Recently, strategies have been developed to solve dynamic simulation and optimization pro...
This chapter presents the "simultaneous design approach" which is an eminently complex process, as d...
Abstract: "The application of recently developed process optimization strategies is motivated and re...
Presents an introduction of pde constrained optimization. This book provides a precise functional an...
We are interested in a situation where a large number of problems of some common type must be solved...
This thesis aims to develop and implement both nonlinear and linear distributed optimization methods...
Sequential approximate optimization (SAO) methods aimed at structural optimization often use recipro...
The problem of determining whether quadratic programming models possess either unique or multiple op...
The problem of determining whether quadratic programming models possess either unique or multiple op...
Sequential approximate optimization (SAO) methods aimed at structural optimization often use recipro...
AbstractIn this paper, efficient simultaneous strategies are presented for the optimization of pract...
In this work, we consider the relevant class of Standard Quadratic Programming problems and we propo...
This book results from the authors work done on simulation based optimization problems at the Depart...
This book results from the authors work done on simulation based optimization problems at the Depart...
We describe a method for solving large-scale general quadratic programming problems. Our method is b...
Abstract: "Recently, strategies have been developed to solve dynamic simulation and optimization pro...
This chapter presents the "simultaneous design approach" which is an eminently complex process, as d...
Abstract: "The application of recently developed process optimization strategies is motivated and re...
Presents an introduction of pde constrained optimization. This book provides a precise functional an...
We are interested in a situation where a large number of problems of some common type must be solved...
This thesis aims to develop and implement both nonlinear and linear distributed optimization methods...
Sequential approximate optimization (SAO) methods aimed at structural optimization often use recipro...
The problem of determining whether quadratic programming models possess either unique or multiple op...
The problem of determining whether quadratic programming models possess either unique or multiple op...
Sequential approximate optimization (SAO) methods aimed at structural optimization often use recipro...
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