# Nonmonotone strategy for minimization of quadratics with simple constraints

M. A. Diniz-Ehrhardt; Zdeněk Dostál; M. A. Gomes-Ruggiero; J. M. Martínez; Sandra Augusta Santos

Applications of Mathematics (2001)

- Volume: 46, Issue: 5, page 321-338
- ISSN: 0862-7940

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topDiniz-Ehrhardt, M. A., et al. "Nonmonotone strategy for minimization of quadratics with simple constraints." Applications of Mathematics 46.5 (2001): 321-338. <http://eudml.org/doc/33090>.

@article{Diniz2001,

abstract = {An algorithm for quadratic minimization with simple bounds is introduced, combining, as many well-known methods do, active set strategies and projection steps. The novelty is that here the criterion for acceptance of a projected trial point is weaker than the usual ones, which are based on monotone decrease of the objective function. It is proved that convergence follows as in the monotone case. Numerical experiments with bound-constrained quadratic problems from CUTE collection show that the modified method is in practice slightly more efficient than its monotone counterpart and has a performance superior to the well-known code LANCELOT for this class of problems.},

author = {Diniz-Ehrhardt, M. A., Dostál, Zdeněk, Gomes-Ruggiero, M. A., Martínez, J. M., Santos, Sandra Augusta},

journal = {Applications of Mathematics},

keywords = {quadratic programming; conjugate gradients; active set methods; quadratic programming; conjugate gradients; active set methods; projection method; convergence; numerical experiments},

language = {eng},

number = {5},

pages = {321-338},

publisher = {Institute of Mathematics, Academy of Sciences of the Czech Republic},

title = {Nonmonotone strategy for minimization of quadratics with simple constraints},

url = {http://eudml.org/doc/33090},

volume = {46},

year = {2001},

}

TY - JOUR

AU - Diniz-Ehrhardt, M. A.

AU - Dostál, Zdeněk

AU - Gomes-Ruggiero, M. A.

AU - Martínez, J. M.

AU - Santos, Sandra Augusta

TI - Nonmonotone strategy for minimization of quadratics with simple constraints

JO - Applications of Mathematics

PY - 2001

PB - Institute of Mathematics, Academy of Sciences of the Czech Republic

VL - 46

IS - 5

SP - 321

EP - 338

AB - An algorithm for quadratic minimization with simple bounds is introduced, combining, as many well-known methods do, active set strategies and projection steps. The novelty is that here the criterion for acceptance of a projected trial point is weaker than the usual ones, which are based on monotone decrease of the objective function. It is proved that convergence follows as in the monotone case. Numerical experiments with bound-constrained quadratic problems from CUTE collection show that the modified method is in practice slightly more efficient than its monotone counterpart and has a performance superior to the well-known code LANCELOT for this class of problems.

LA - eng

KW - quadratic programming; conjugate gradients; active set methods; quadratic programming; conjugate gradients; active set methods; projection method; convergence; numerical experiments

UR - http://eudml.org/doc/33090

ER -

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