All Classes

Class	Description
AbstractConvergenceChecker<P>	Base class for all convergence checker implementations.
AbstractEvaluation	An implementation of LeastSquaresProblem.Evaluation that is designed for extension.
AbstractOptimizationProblem<P>	Base class for implementing optimization problems.
AbstractSimplex	This class implements the simplex concept.
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.
BaseMultiStartMultivariateOptimizer<P>	Base class multi-start optimizer for a multivariate function.
BaseMultivariateOptimizer<P>	Base class for implementing optimizers for multivariate functions.
BaseOptimizer<P>	Base class for implementing optimizers.
BOBYQAOptimizer	Powell's BOBYQA algorithm.
BoundedConstraint	Constraint with lower and upper bounds: \(l \le f(x) \le u\).
BracketFinder	Provide an interval that brackets a local optimum of a function.
BrentOptimizer	For a function defined on some interval (lo, hi), this class finds an approximation x to the point at which the function attains its minimum.
CMAESOptimizer	An implementation of the active Covariance Matrix Adaptation Evolution Strategy (CMA-ES) for non-linear, non-convex, non-smooth, global function minimization.
CMAESOptimizer.PopulationSize	Population size.
CMAESOptimizer.Sigma	Input sigma values.
Constraint	Generic constraint.
ConstraintOptimizer	Abstract Constraint Optimizer.
ConvergenceChecker<P>	This interface specifies how to check if an optimization algorithm has converged.
ConvergenceCheckerAndMultiplexer<P>	Multiplexer for ConvergenceChecker, checking all the checkers converged.
ConvergenceCheckerOrMultiplexer<P>	Multiplexer for ConvergenceChecker, checking one of the checkers converged.
EqualityConstraint	Equality Constraint.
EvaluationRmsChecker	Check if an optimization has converged based on the change in computed RMS.
GaussNewtonOptimizer	Gauss-Newton least-squares solver.
GoalType	Goal type for an optimization problem (minimization or maximization of a scalar function.
GradientMultivariateOptimizer	Base class for implementing optimizers for multivariate scalar differentiable functions.
InequalityConstraint	Inequality Constraint with lower bound only: \(l \le f(x)\).
InitialGuess	Starting point (first guess) of the optimization procedure.
KarushKuhnTuckerSolver<T>	Karush–Kuhn–Tucker Solver.
LagrangeSolution	Container for Lagrange t-uple.
LeastSquaresAdapter	An adapter that delegates to another implementation of LeastSquaresProblem.
LeastSquaresBuilder	A mutable builder for LeastSquaresProblems.
LeastSquaresConverter	This class converts vectorial objective functions to scalar objective functions when the goal is to minimize them.
LeastSquaresFactory	A Factory for creating LeastSquaresProblems.
LeastSquaresOptimizer	An algorithm that can be applied to a non-linear least squares problem.
LeastSquaresOptimizer.Optimum	The optimum found by the optimizer.
LeastSquaresProblem	The data necessary to define a non-linear least squares problem.
LeastSquaresProblem.Evaluation	An evaluation of a LeastSquaresProblem at a particular point.
LevenbergMarquardtOptimizer	This class solves a least-squares problem using the Levenberg-Marquardt algorithm.
LinearBoundedConstraint	A set of linear inequality constraints expressed as ub>Ax>lb.
LinearConstraint	A linear constraint for a linear optimization problem.
LinearConstraintSet	Class that represents a set of linear constraints.
LinearEqualityConstraint	A set of linear equality constraints given as Ax = b.
LinearInequalityConstraint	Set of linear inequality constraints expressed as \( A x \gt B\).
LinearObjectiveFunction	An objective function for a linear optimization problem.
LinearOptimizer	Base class for implementing linear optimizers.
LineSearch	Class for finding the minimum of the objective function along a given direction.
LocalizedOptimFormats	Enumeration for localized messages formats used in exceptions messages.
MaxEval	Maximum number of evaluations of the function to be optimized.
MaxIter	Maximum number of iterations performed by an (iterative) algorithm.
MultiDirectionalSimplex	This class implements the multi-directional direct search method.
MultiStartMultivariateOptimizer	Multi-start optimizer.
MultiStartUnivariateOptimizer	Special implementation of the UnivariateOptimizer interface adding multi-start features to an existing optimizer.
MultivariateFunctionMappingAdapter	Adapter for mapping bounded MultivariateFunction to unbounded ones.
MultivariateFunctionPenaltyAdapter	Adapter extending bounded MultivariateFunction to an unbouded domain using a penalty function.
MultivariateJacobianFunction	A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).
MultivariateOptimizer	Base class for a multivariate scalar function optimizer.
NelderMeadSimplex	This class implements the Nelder-Mead simplex algorithm.
NonLinearConjugateGradientOptimizer	Non-linear conjugate gradient optimizer.
NonLinearConjugateGradientOptimizer.Formula	Available choices of update formulas for the updating the parameter that is used to compute the successive conjugate search directions.
NonLinearConjugateGradientOptimizer.IdentityPreconditioner	Default identity preconditioner.
NonNegativeConstraint	A constraint for a linear optimization problem indicating whether all variables must be restricted to non-negative values.
ObjectiveFunction	Scalar function to be optimized.
ObjectiveFunctionGradient	Gradient of the scalar function to be optimized.
OptimizationData	Marker interface.
OptimizationProblem<P>	Common settings for all optimization problems.
ParameterValidator	Interface for validating a set of model parameters.
PivotSelectionRule	Pivot selection rule to the use for a Simplex solver.
PointValuePair	This class holds a point and the value of an objective function at that point.
PointVectorValuePair	This class holds a point and the vectorial value of an objective function at that point.
PowellOptimizer	Powell's algorithm.
Preconditioner	This interface represents a preconditioner for differentiable scalar objective function optimizers.
QPOptimizer	Quadratic programming Optimizater.
QuadraticFunction	Given P, Q, d, implements \(\frac{1}{2}x^T P X + Q^T x + d\).
Relationship	Types of relationships between two cells in a Solver LinearConstraint.
SearchInterval	Search interval and (optional) start value.
SequentialGaussNewtonOptimizer	Sequential Gauss-Newton least-squares solver.
SimpleBounds	Simple optimization constraints: lower and upper bounds.
SimplePointChecker<P extends Pair<double[],? extends Object>>	Simple implementation of the ConvergenceChecker interface using only point coordinates.
SimpleUnivariateValueChecker	Simple implementation of the ConvergenceChecker interface that uses only objective function values.
SimpleValueChecker	Simple implementation of the ConvergenceChecker interface using only objective function values.
SimpleVectorValueChecker	Simple implementation of the ConvergenceChecker interface using only objective function values.
SimplexOptimizer	This class implements simplex-based direct search optimization.
SimplexSolver	Solves a linear problem using the "Two-Phase Simplex" method.
SolutionCallback	A callback object that can be provided to a linear optimizer to keep track of the best solution found.
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.
UnivariateObjectiveFunction	Scalar function to be optimized.
UnivariateOptimizer	Base class for a univariate scalar function optimizer.
UnivariatePointValuePair	This class holds a point and the value of an objective function at this point.
ValueAndJacobianFunction	A interface for functions that compute a vector of values and can compute their derivatives (Jacobian).
VectorDifferentiableFunction	A MultivariateFunction that also has a defined gradient and Hessian.