Package org.hipparchus.optim.nonlinear.vector.constrained

package org.hipparchus.optim.nonlinear.vector.constrained

This package provides algorithms that minimize the residuals between observations and model values. The least-squares optimizers minimize the distance (called cost or χ²) between model and observations.
Algorithms in this category need access to a problem (represented by a LeastSquaresProblem). Such a model predicts a set of values which the algorithm tries to match with a set of given set of observed values.
The problem can be created progressively using a builder or it can be created at once using a factory.

Since:

3.1

Class	Description
AbstractSQPOptimizer	Abstract class for Sequential Quadratic Programming solvers
ADMMQPConvergenceChecker	Convergence Checker for ADMM QP Optimizer.
ADMMQPKKT	Alternative Direction Method of Multipliers Solver.
ADMMQPModifiedRuizEquilibrium	TBD.
ADMMQPOptimizer	Alternating Direction Method of Multipliers Quadratic Programming Optimizer. \[ min \frac{1}{2} X^T Q X + G X a\\ A X = B_1\\ B X \ge B_2\\ l_b \le C X \le u_b \] Algorithm based on paper:"An Operator Splitting Solver for Quadratic Programs(Bartolomeo Stellato, Goran Banjac, Paul Goulart, Alberto Bemporad, Stephen Boyd,February 13 2020)"
ADMMQPOption	Container for ADMMQPOptimizer settings.
ADMMQPSolution	Internal Solution for ADMM QP Optimizer.
BoundedConstraint	Constraint with lower and upper bounds: \(l \le f(x) \le u\).
Constraint	Generic constraint.
ConstraintOptimizer	Abstract Constraint Optimizer.
EqualityConstraint	Equality Constraint.
InequalityConstraint	Inequality Constraint with lower bound only: \(l \le f(x)\).
KarushKuhnTuckerSolver<T>	Karush–Kuhn–Tucker Solver.
LagrangeSolution	Container for Lagrange t-uple.
LinearBoundedConstraint	A set of linear inequality constraints expressed as ub>Ax>lb.
LinearEqualityConstraint	A set of linear equality constraints given as Ax = b.
LinearInequalityConstraint	Set of linear inequality constraints expressed as \( A x \gt B\).
QPOptimizer	Quadratic programming Optimizater.
QuadraticFunction	Given P, Q, d, implements \(\frac{1}{2}x^T P X + Q^T x + d\).
SQPOptimizerGM	Sequential Quadratic Programming Optimizer.
SQPOptimizerS	Sequential Quadratic Programming Optimizer.
SQPOption	Parameter for SQP Algorithm.
TwiceDifferentiableFunction	A MultivariateFunction that also has a defined gradient and Hessian.
VectorDifferentiableFunction	A MultivariateFunction that also has a defined gradient and Hessian.