Modifier and Type | Interface and Description |
---|---|
interface |
Maxmizer<P extends OptimProblem,S extends MaximizationSolution<?>>
This interface represents an optimization algorithm that maximizers a real valued objective
function, one or multi dimension.
|
interface |
Minimizer<P extends OptimProblem,S extends MinimizationSolution<?>>
This interface represents an optimization algorithm that minimizes a real valued objective
function, one or multi dimension.
|
Modifier and Type | Interface and Description |
---|---|
interface |
BoxMinimizer<P extends BoxOptimProblem,S extends MinimizationSolution<?>>
A box minimizer solves a
BoxOptimProblem . |
interface |
ConstrainedMinimizer<P extends ConstrainedOptimProblem,S extends MinimizationSolution<?>>
A constrained minimizer solves a constrained optimization problem, namely,
ConstrainedOptimProblem . |
Modifier and Type | Class and Description |
---|---|
class |
SubProblemMinimizer
This minimizer solves a constrained optimization sub-problem where the values
for some variables are held fixed for the original optimization problem.
|
Modifier and Type | Class and Description |
---|---|
class |
CSDPMinimizer
Implements the CSDP algorithm for semidefinite programming problem with equality constraints.
|
class |
HomogeneousPathFollowingMinimizer
This implementation solves a Semi-Definite Programming problem using the Homogeneous Self-Dual
Path-Following algorithm.
|
class |
PrimalDualPathFollowingMinimizer
The Primal-Dual Path-Following algorithm is an interior point method that solves Semi-Definite
Programming problems.
|
Modifier and Type | Class and Description |
---|---|
class |
PrimalDualInteriorPointMinimizer
Solves a Dual Second Order Conic Programming problem using the Primal Dual
Interior Point algorithm.
|
Modifier and Type | Interface and Description |
---|---|
interface |
LPSolver<P extends LPProblem,S extends LPSolution<?>>
An LP solver solves a Linear Programming (LP) problem.
|
Modifier and Type | Interface and Description |
---|---|
interface |
LPSimplexSolver<P extends LPProblem>
A simplex solver works toward an LP solution by sequentially applying Jordan exchange to a simplex table.
|
Modifier and Type | Class and Description |
---|---|
class |
FerrisMangasarianWrightPhase2
This implementation solves a canonical linear programming problem that does not need preprocessing its simplex table.
|
class |
LPCanonicalSolver
This is an LP solver that solves a canonical LP problem in the following form.
|
class |
LPRevisedSimplexSolver |
class |
LPTwoPhaseSolver
This implementation solves a linear programming problem,
LPProblem , using a two-step approach. |
Modifier and Type | Interface and Description |
---|---|
interface |
QPMinimizer
A typedef for QP minimizer.
|
Modifier and Type | Class and Description |
---|---|
class |
QPDualActiveSetMinimizer
This implementation solves a Quadratic Programming problem using the dual
active set algorithm.
|
class |
QPPrimalActiveSetMinimizer
This implementation solves a Quadratic Programming problem using the Primal
Active Set algorithm.
|
Modifier and Type | Class and Description |
---|---|
class |
QPbySOCPMinimizer
We first convert a QP problem to an equivalent SOCP problem and then solve it
using an SOCP solver.
|
Modifier and Type | Class and Description |
---|---|
class |
BoxGeneralizedSimulatedAnnealingMinimizer
This is an extension to
GeneralizedSimulatedAnnealingMinimizer , which allows adding box
constraints to bound solutions. |
Modifier and Type | Class and Description |
---|---|
class |
PenaltyMethodMinimizer
The penalty method is an algorithm for solving a constrained minimization problem with general
constraints.
|
Modifier and Type | Class and Description |
---|---|
class |
SQPActiveSetMinimizer
Sequential quadratic programming (SQP) is an iterative method for nonlinear
optimization.
|
class |
SQPActiveSetOnlyInequalityConstraintMinimizer
This implementation is a modified version of Algorithm 15.2 in the reference
to solve a general constrained optimization problem with only inequality
constraints.
|
Modifier and Type | Class and Description |
---|---|
class |
SQPActiveSetOnlyEqualityConstraint1Minimizer
This implementation is a modified version of Algorithm 15.1 in the reference to solve a general constrained optimization problem with only equality constraints.
|
class |
SQPActiveSetOnlyEqualityConstraint2Minimizer
This particular implementation of
SQPActiveSetOnlyEqualityConstraint1Minimizer uses SQPASEVariation2 . |
Modifier and Type | Interface and Description |
---|---|
interface |
IPMinimizer<T extends IPProblem,S extends MinimizationSolution<Vector>>
An Integer Programming minimizer minimizes an objective function subject to equality/inequality
constraints as well as integral constraints.
|
Modifier and Type | Class and Description |
---|---|
class |
BruteForceIPMinimizer
This implementation solves an integral constrained minimization problem by
brute force search for all possible integer combinations.
|
Modifier and Type | Class and Description |
---|---|
class |
ILPBranchAndBoundMinimizer
This is a Branch-and-Bound algorithm that solves Integer Linear Programming problems.
|
Modifier and Type | Class and Description |
---|---|
class |
GomoryMixedCutMinimizer
This cutting-plane implementation uses Gomory's mixed cut method.
|
class |
GomoryPureCutMinimizer
This cutting-plane implementation uses Gomory's pure cut method for pure integer programming,
in which all variables are integral.
|
class |
SimplexCuttingPlaneMinimizer
The use of cutting planes to solve Mixed Integer Linear Programming (MILP) problems was introduced by Ralph E Gomory.
|
Modifier and Type | Class and Description |
---|---|
class |
DEOptim
Differential Evolution (DE) is a global optimization method.
|
Modifier and Type | Class and Description |
---|---|
class |
GlobalSearchByLocalMinimizer
This minimizer is a global optimization method.
|
Modifier and Type | Class and Description |
---|---|
class |
SimpleGridMinimizer
This minimizer is a simple global optimization method.
|
Modifier and Type | Interface and Description |
---|---|
interface |
MinMaxMinimizer<T>
A minmax minimizer minimizes a minmax problem.
|
Modifier and Type | Class and Description |
---|---|
class |
LeastPth<T>
The least p-th minmax algorithm minimizes the maximal error/loss (function):
\[
\min_x \max_{\omega \in S} e(x, \omega)
\]
\(e(x, \omega)\) is the error or loss function.
|
Modifier and Type | Interface and Description |
---|---|
interface |
IterativeMinimizer<P extends OptimProblem>
This is an iterative multivariate minimizer.
|
interface |
MultivariateMinimizer<P extends OptimProblem,S extends MinimizationSolution<Vector>>
This is a minimizer that minimizes a multivariate function or a Vector function.
|
Modifier and Type | Class and Description |
---|---|
class |
BruteForceMinimizer<R extends Comparable<R>>
This implementation solves an unconstrained minimization problem by
brute force search for all given possible values.
|
class |
DoubleBruteForceMinimizer
This implementation solves an unconstrained minimization problem by
brute force search for all given possible values.
|
Modifier and Type | Class and Description |
---|---|
class |
GeneralizedSimulatedAnnealingMinimizer
Tsallis and Stariolo (1996) proposed this variant of
SimulatedAnnealingMinimizer (SA). |
class |
SimulatedAnnealingMinimizer
Simulated Annealing is a global optimization meta-heuristic that is inspired by annealing in
metallurgy.
|
Modifier and Type | Interface and Description |
---|---|
interface |
IterativeC2Minimizer
This is a minimizer that minimizes a twice continuously differentiable, multivariate function.
|
Modifier and Type | Class and Description |
---|---|
class |
IterativeC2Maximizer
A maximization problem is simply minimizing the negative of the objective function.
|
class |
NelderMeadMinimizer
The Nelder-Mead method is a nonlinear optimization technique, which is well-defined for twice
differentiable and unimodal problems.
|
Modifier and Type | Class and Description |
---|---|
class |
ConjugateGradientMinimizer
A conjugate direction optimization method is performed by using
sequential line search along directions that bear a strict mathematical relationship to one another.
|
class |
FletcherReevesMinimizer
The Fletcher-Reeves method is a variant of the Conjugate-Gradient method.
|
class |
PowellMinimizer
Powell's algorithm, starting from an initial point, performs a series
of line searches in one iteration.
|
class |
ZangwillMinimizer
Zangwill's algorithm is an improved version of Powell's algorithm.
|
Modifier and Type | Interface and Description |
---|---|
interface |
LineSearch
A line search is often used in another minimization algorithm to improve the current solution in one iteration step.
|
Modifier and Type | Class and Description |
---|---|
class |
FletcherLineSearch
This is Fletcher's inexact line search method.
|
Modifier and Type | Class and Description |
---|---|
class |
BFGSMinimizer
The Broyden-Fletcher-Goldfarb-Shanno method is a quasi-Newton method
to solve unconstrained nonlinear optimization problems.
|
class |
DFPMinimizer
The Davidon-Fletcher-Powell method is a quasi-Newton method
to solve unconstrained nonlinear optimization problems.
|
class |
HuangMinimizer
Huang's updating formula is a family of formulas which encompasses
the rank-one, DFP, BFGS as well as some other formulas.
|
class |
McCormickMinimizer
Deprecated.
the McCormick algorithm does not seem to work well; need further investigation; don't use it. TODO. Use
BFGSMinimizer instead. |
class |
PearsonMinimizer
This is the Pearson method.
|
class |
QuasiNewtonMinimizer
The Quasi-Newton methods in optimization are for finding local maxima and minima of functions.
|
class |
RankOneMinimizer
The Rank One method is a quasi-Newton method
to solve unconstrained nonlinear optimization problems.
|
Modifier and Type | Class and Description |
---|---|
class |
FirstOrderMinimizer
This implements the steepest descent line search using the first order expansion of the Taylor's series.
|
protected static class |
GaussNewtonMinimizer.MySteepestDescent |
class |
NewtonRaphsonMinimizer
The Newton-Raphson method is a second order steepest descent method that is based on
the quadratic approximation of the Taylor series.
|
class |
SteepestDescentMinimizer
A steepest descent algorithm finds the minimum by moving along the negative of the steepest
gradient direction.
|
Modifier and Type | Interface and Description |
---|---|
interface |
UnivariateMinimizer
A univariate minimizer minimizes a univariate function.
|
Modifier and Type | Class and Description |
---|---|
class |
GridSearchMinimizer
This performs a grid search to find the minimum of a univariate function.
|
Modifier and Type | Class and Description |
---|---|
class |
BracketSearchMinimizer
This class provides implementation support for those univariate optimization algorithms that are based on bracketing.
|
class |
BrentMinimizer
Brent's algorithm is the preferred method for finding the minimum of a univariate function.
|
class |
FibonaccMinimizer
The Fibonacci search is a dichotomous search where a bracketing interval is sub-divided by the Fibonacci ratio.
|
class |
GoldenMinimizer
This is the golden section univariate minimization algorithm.
|
Modifier and Type | Interface and Description |
---|---|
interface |
CetaMaximizer
Defines an algorithm to search for the maximal C(η).
|
Modifier and Type | Class and Description |
---|---|
class |
BrentCetaMaximizer
Searches for the maximal point of C(η) by
Brent's method.
|
class |
CombinedCetaMaximizer
Searches the maximum C(η) by an array of given maximizers, being
tried in sequence.
|
class |
GridSearchCetaMaximizer
Searches (by brute force) for the maximal point of C(η) among a
grid of values.
|
Copyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.