Derivative-free nonlinear optimization filter simplex
Aldina Correia; João Matias; Pedro Mestre; Carlos Serodio
International Journal of Applied Mathematics and Computer Science (2010)
- Volume: 20, Issue: 4, page 679-688
- ISSN: 1641-876X
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topAldina Correia, et al. "Derivative-free nonlinear optimization filter simplex." International Journal of Applied Mathematics and Computer Science 20.4 (2010): 679-688. <http://eudml.org/doc/208017>.
@article{AldinaCorreia2010,
abstract = {The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.},
author = {Aldina Correia, João Matias, Pedro Mestre, Carlos Serodio},
journal = {International Journal of Applied Mathematics and Computer Science},
keywords = {nonlinear constrained optimization; filter methods; direct search methods},
language = {eng},
number = {4},
pages = {679-688},
title = {Derivative-free nonlinear optimization filter simplex},
url = {http://eudml.org/doc/208017},
volume = {20},
year = {2010},
}
TY - JOUR
AU - Aldina Correia
AU - João Matias
AU - Pedro Mestre
AU - Carlos Serodio
TI - Derivative-free nonlinear optimization filter simplex
JO - International Journal of Applied Mathematics and Computer Science
PY - 2010
VL - 20
IS - 4
SP - 679
EP - 688
AB - The filter method is a technique for solving nonlinear programming problems. The filter algorithm has two phases in each iteration. The first one reduces a measure of infeasibility, while in the second the objective function value is reduced. In real optimization problems, usually the objective function is not differentiable or its derivatives are unknown. In these cases it becomes essential to use optimization methods where the calculation of the derivatives or the verification of their existence is not necessary: direct search methods or derivative-free methods are examples of such techniques. In this work we present a new direct search method, based on simplex methods, for general constrained optimization that combines the features of simplex and filter methods. This method neither computes nor approximates derivatives, penalty constants or Lagrange multipliers.
LA - eng
KW - nonlinear constrained optimization; filter methods; direct search methods
UR - http://eudml.org/doc/208017
ER -
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