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Quadratic programs with hollows
Mathematical Programming, 2017zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Boshi Yang +2 more
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A quadratic programming algorithm
Zeitschrift für Operations Research, 1988Summary: By using conjugate directions a method for solving convex quadratic programming problems is developed. The algorithm generates a sequence of feasible solutions and terminates after a finite number of iterations. Extensions of the algorithm for nonconvex and large structured quadratic programming problems are discussed.
Michael J. Best, Klaus Ritter 0002
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Management Science, 1971
A procedure based on Lemke's algorithm is developed which either computes stationary points for general quadratic programs or else shows that the program has no optimum. If a general quadratic program has an optimum and satisfies a non-degeneracy condition then it is demonstrated that there are an odd number of stationary points.
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A procedure based on Lemke's algorithm is developed which either computes stationary points for general quadratic programs or else shows that the program has no optimum. If a general quadratic program has an optimum and satisfies a non-degeneracy condition then it is demonstrated that there are an odd number of stationary points.
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SIAM Journal on Optimization, 2007
We introduce and study a special class of nonconvex quadratic problems in which the objective and constraint functions have the form $f(\boldmath $X$)={Tr}(\boldmath $X$^T \boldmath $A$ \boldmath $X$) + 2 Tr(\boldmath $B$^T \boldmath $X$) +c, \boldmath $X$ \in {\real R}^{n \times r}$.
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We introduce and study a special class of nonconvex quadratic problems in which the objective and constraint functions have the form $f(\boldmath $X$)={Tr}(\boldmath $X$^T \boldmath $A$ \boldmath $X$) + 2 Tr(\boldmath $B$^T \boldmath $X$) +c, \boldmath $X$ \in {\real R}^{n \times r}$.
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Controlled perturbations for quadratically constrained quadratic programs
Mathematical Programming, 1986Consider a minimization problem of a convex quadratic function of several variables over a set of inequality constraints of the same type of function. The dual program is a maximization problem with a concave objective function and a set of constraints that are essentially linear.
Shu-Cherng Fang, J. R. Rajasekera
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Approximation Algorithms for Quadratic Programming
Journal of Combinatorial Optimization, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Minyue Fu 0001 +2 more
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On Quadratically Constrained Quadratic Programs and their Semidefinite Program Relaxations
2022Quadratically constrained quadratic programs (QCQPs) are a fundamental class of optimization problems. In a QCQP, we are asked to minimize a (possibly nonconvex) quadratic function subject to a number of (possibly nonconvex) quadratic constraints.
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, 2020 U ovom radu govorimo što je to kvadratno programiranje, formuliramo problem i iskazujemo neka svojstva teorije uvjetne optimizacije. Proučavamo probleme kvadratnog programiranja s jednakosnim i nejednakosnim uvjetima i za obe klase iskazujemo koja su ...
Sladović, Sara
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Programming with a Quadratic Constraint
Management Science, 1966A method is given for maximizing a linear function subject to a quadratic and a number of linear constraints. The method differs from general convex programming methods by terminating in a finite number of iterations and is actually an application of the Simplex and dual methods for quadratic programming to parametric quadratic programming problems ...
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Quadratic programming with quadratic constraints
Naval Research Logistics Quarterly, 1972AbstractA program with a quadratic objective function and quadratic constraints is considered. Two duals to such programs are provided, and an algorithm is presented based upon approximations to the duals. The algorithm consists of a sequence of linear programs and programs involving the optimization of a quadratic function either unconstrained or ...
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