Uses of Class
dev.nm.analysis.function.rn2r1.QuadraticFunction

Packages that use QuadraticFunction

Package	Description
dev.nm.analysis.function.rn2r1
dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp	Quadratic programming with explicit objective and constraint conventions.
dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem

Uses of QuadraticFunction in dev.nm.analysis.function.rn2r1

Constructors in dev.nm.analysis.function.rn2r1 with parameters of type QuadraticFunction

Constructor and Description
QuadraticFunction(QuadraticFunction f) Copy constructor.

Uses of QuadraticFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp

Methods in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp with parameters of type QuadraticFunction

Modifier and Type	Method and Description
static QPSolution	QPSimpleMinimizer.solve(QuadraticFunction f) Solves an unconstrained quadratic programming problem of this form. \[ \min_x \left \{ \frac{1}{2} \times x'Hx + x'p \right \} \]
static QPSolution	QPSimpleMinimizer.solve(QuadraticFunction f, double epsilon) Solves an unconstrained quadratic programming problem of this form. \[ \min_x \left \{ \frac{1}{2} \times x'Hx + x'p \right \} \]
static QPSolution	QPSimpleMinimizer.solve(QuadraticFunction f, LinearEqualityConstraints equal) Solves a quadratic programming problem subject to equality constraints. \[ \min_x \left \{ \frac{1}{2} \times x'Hx + x'p \right \}, Ax = b \]
static QPSolution	QPSimpleMinimizer.solve(QuadraticFunction f, LinearEqualityConstraints equal, double epsilon) Solves a quadratic programming problem subject to equality constraints. \[ \min_x \left \{ \frac{1}{2} \times x'Hx + x'p \right \}, Ax = b \]

Uses of QuadraticFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem

Subclasses of QuadraticFunction in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem

Modifier and Type	Class and Description
class	QPProblemOnlyEqualityConstraints A quadratic programming problem with only equality constraints can be converted into a equivalent quadratic programming problem without constraints, hence a mere quadratic function.

Methods in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem that return QuadraticFunction

Modifier and Type	Method and Description
QuadraticFunction	QPProblem.f()

Constructors in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.problem with parameters of type QuadraticFunction

Constructor and Description
QPProblem(QuadraticFunction f, LinearEqualityConstraints equal, LinearGreaterThanConstraints greater) Construct a quadratic programming problem with linear equality and greater-than-or-equal-to constraints.
QPProblem(QuadraticFunction f, LinearEqualityConstraints equal, LinearGreaterThanConstraints greater, LinearLessThanConstraints less) Construct a quadratic programming problem.
QPProblem(QuadraticFunction f, LinearEqualityConstraints equal, LinearLessThanConstraints less) Construct a quadratic programming problem with linear equality and less-than-or-equal-to constraints.
QPProblem(QuadraticFunction f, LinearGreaterThanConstraints greater) Construct a quadratic programming problem with linear greater-than-or-equal-to constraints.
QPProblem(QuadraticFunction f, LinearGreaterThanConstraints greater, LinearLessThanConstraints less) Construct a quadratic programming problem with linear inequality constraints.
QPProblem(QuadraticFunction f, LinearLessThanConstraints less) Construct a quadratic programming problem with linear less-than-or-equal-to constraints.
QPProblemOnlyEqualityConstraints(QuadraticFunction f, LinearEqualityConstraints equal) Construct a quadratic programming problem with only equality constraints.