Results 241 to 250 of about 6,923,335 (304)
Some of the next articles are maybe not open access.
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.
openaire +1 more source
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.
openaire +1 more source
Engineering optimization (Print), 2018
In this article, a superlinearly convergent trust region–sequential quadratic programming approach is first proposed, developed and investigated for nonlinear systems based on nonlinear model predictive control.
Zhongbo Sun +4 more
semanticscholar +1 more source
In this article, a superlinearly convergent trust region–sequential quadratic programming approach is first proposed, developed and investigated for nonlinear systems based on nonlinear model predictive control.
Zhongbo Sun +4 more
semanticscholar +1 more source
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}$.
openaire +1 more source
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}$.
openaire +1 more source
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.
openaire +1 more source
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 ...
openaire +1 more source
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 ...
openaire +1 more source
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
openaire +1 more source
Extended formulations in mixed integer conic quadratic programming
Mathematical Programming Computation, 2015In this paper we consider the use of extended formulations in LP-based algorithms for mixed integer conic quadratic programming (MICQP). Extended formulations have been used by Vielma et al. (INFORMS J Comput 20: 438–450, 2008) and Hijazi et al.
J. Vielma +3 more
semanticscholar +1 more source
Approximation Algorithms for Quadratic Programming
Journal of Combinatorial Optimization, 1998zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Minyue Fu 0001 +2 more
openaire +2 more sources
The Indefinite Quadratic Programming Problem
Operations Research, 1979We develop several algorithms that obtain the global optimum to the indefinite quadratic programming problem. A generalized Benders cut method is employed. These algorithms all possess ϵ-finite convergence. To obtain finite convergence, we develop exact cuts, which are locally precise representations of a reduced objective.
openaire +1 more source