# The SUBQ method in quadratic programming

Mathematica Applicanda (1980)

- Volume: 8, Issue: 16
- ISSN: 1730-2668

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topGrażyna Hille. "The SUBQ method in quadratic programming." Mathematica Applicanda 8.16 (1980): null. <http://eudml.org/doc/292961>.

@article{GrażynaHille1980,

abstract = {Author's summary: "In linear programming the simple upper bound method (SUB in short) is well known. It is a modification of the simplex method which finds a minimum of the target function on an admissible set with some additional conditions of the form β≤x≤α imposed on x. "In this paper we present a method which solves the problem of minimization of a quadratic, convex target function on an admissible set defined by conditions of the form β≤x≤α. It is a modification of the C. E. Lemke algorithm [Management Sci. 8 (1961/62), 442–453; MR0148483] for problems of quadratic programming. Because of the special form of the conditions defining the admissible set this method is in a sense a counterpart of the SUB method in linear programming. Therefore we call the algorithm the SUBQ algorithm (the simple upper bound algorithm for quadratic programming). "In Section 2 we give a description of the method based mainly on a geometric interpretation. In Section 3 we present the algorithm and in Section 4 we give a proof of the convergence of the method.''},

author = {Grażyna Hille},

journal = {Mathematica Applicanda},

keywords = {Quadratic programming},

language = {eng},

number = {16},

pages = {null},

title = {The SUBQ method in quadratic programming},

url = {http://eudml.org/doc/292961},

volume = {8},

year = {1980},

}

TY - JOUR

AU - Grażyna Hille

TI - The SUBQ method in quadratic programming

JO - Mathematica Applicanda

PY - 1980

VL - 8

IS - 16

SP - null

AB - Author's summary: "In linear programming the simple upper bound method (SUB in short) is well known. It is a modification of the simplex method which finds a minimum of the target function on an admissible set with some additional conditions of the form β≤x≤α imposed on x. "In this paper we present a method which solves the problem of minimization of a quadratic, convex target function on an admissible set defined by conditions of the form β≤x≤α. It is a modification of the C. E. Lemke algorithm [Management Sci. 8 (1961/62), 442–453; MR0148483] for problems of quadratic programming. Because of the special form of the conditions defining the admissible set this method is in a sense a counterpart of the SUB method in linear programming. Therefore we call the algorithm the SUBQ algorithm (the simple upper bound algorithm for quadratic programming). "In Section 2 we give a description of the method based mainly on a geometric interpretation. In Section 3 we present the algorithm and in Section 4 we give a proof of the convergence of the method.''

LA - eng

KW - Quadratic programming

UR - http://eudml.org/doc/292961

ER -

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