Uses of Interface
dev.nm.solver.Minimizer
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Uses of Minimizer in dev.nm.root.univariate
Subinterfaces of Minimizer in dev.nm.root.univariate Modifier and Type Interface Description interface
UnivariateMinimizer
A univariate minimizer minimizes a univariate function.Classes in dev.nm.root.univariate that implement Minimizer Modifier and Type Class Description class
GridSearchMinimizer
This performs a grid search to find the minimum of a univariate function. -
Uses of Minimizer in dev.nm.root.univariate.bracketsearch
Classes in dev.nm.root.univariate.bracketsearch that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained
Subinterfaces of Minimizer in dev.nm.solver.multivariate.constrained Modifier and Type Interface Description interface
BoxMinimizer<P extends BoxOptimProblem,S extends MinimizationSolution<?>>
A box minimizer solves aBoxOptimProblem
.interface
ConstrainedMinimizer<P extends ConstrainedOptimProblem,S extends MinimizationSolution<?>>
A constrained minimizer solves a constrained optimization problem, namely,ConstrainedOptimProblem
.Classes in dev.nm.solver.multivariate.constrained that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.pathfollowing
Classes in dev.nm.solver.multivariate.constrained.convex.sdp.pathfollowing that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.interiorpoint
Classes in dev.nm.solver.multivariate.constrained.convex.sdp.socp.interiorpoint that implement Minimizer Modifier and Type Class Description class
PrimalDualInteriorPointMinimizer
Solves a Dual Second Order Conic Programming problem using the Primal Dual Interior Point algorithm.class
PrimalDualInteriorPointMinimizer1
The SOCP dual problem we are solving here is : \max {\bm b}^T \hat{\bm y} \\ {\rm s.t.} ({\bm A_i^q})^T \hat{\bm y} + {\bm z_i^q} = c_i^q,\ {\bm z_i^q}\in \mathcal{K}_q^{q_i},\ for i\in [n_q];\\ ({\bm A^{\ell}})^T \hat{\bm y} + {\bm z}^{\ell} = c^{\ell},\ {\bm z}^{\ell} \ge 0;\\ ({\bm A^u})^T \hat{\bm y} = c^u;\\ \hat{\bm y} \in \mathbb{R}^m;\ {\bm z}^{\ell}\in \mathbb{R}^{n_{\ell}};\ {\bm z}^u \in \mathbb{R}^{n_u}. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp
Subinterfaces of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp Modifier and Type Interface Description interface
LPSolver<P extends LPProblem,S extends LPSolution<?>>
An LP solver solves a Linear Programming (LP) problem. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver
Subinterfaces of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver Modifier and Type Interface Description interface
LPSimplexSolver<P extends LPProblem>
A simplex solver works toward an LP solution by sequentially applying Jordan exchange to a simplex table.Classes in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.lp.simplex.solver that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.solver
Subinterfaces of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.solver Modifier and Type Interface Description interface
QPMinimizer
A typedef for QP minimizer. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.solver.activeset
Classes in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.solver.activeset that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.solver.socp
Classes in dev.nm.solver.multivariate.constrained.convex.sdp.socp.qp.solver.socp that implement Minimizer Modifier and Type Class Description class
QPbySOCPMinimizer
We first convert a QP problem to an equivalent SOCP problem and then solve it using an SOCP solver.class
QPbySOCPMinimizer1
A QP problem is first converted into an equivalent SOCP problemSOCPGeneralProblem1
and then solve it using an SOCP solverPrimalDualInteriorPointMinimizer1
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Uses of Minimizer in dev.nm.solver.multivariate.constrained.general.box
Classes in dev.nm.solver.multivariate.constrained.general.box that implement Minimizer Modifier and Type Class Description class
BoxGeneralizedSimulatedAnnealingMinimizer
This is an extension toGeneralizedSimulatedAnnealingMinimizer
, which allows adding box constraints to bound solutions. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.general.penaltymethod
Classes in dev.nm.solver.multivariate.constrained.general.penaltymethod that implement Minimizer Modifier and Type Class Description class
PenaltyMethodMinimizer
The penalty method is an algorithm for solving a constrained minimization problem with general constraints. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.general.sqp.activeset
Classes in dev.nm.solver.multivariate.constrained.general.sqp.activeset that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.general.sqp.activeset.equalityconstraint
Classes in dev.nm.solver.multivariate.constrained.general.sqp.activeset.equalityconstraint that implement Minimizer Modifier and Type Class 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 ofSQPActiveSetOnlyEqualityConstraint1Minimizer
usesSQPASEVariation2
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Uses of Minimizer in dev.nm.solver.multivariate.constrained.integer
Subinterfaces of Minimizer in dev.nm.solver.multivariate.constrained.integer Modifier and Type Interface 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. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.integer.bruteforce
Classes in dev.nm.solver.multivariate.constrained.integer.bruteforce that implement Minimizer Modifier and Type Class Description class
BruteForceIPMinimizer
This implementation solves an integral constrained minimization problem by brute force search for all possible integer combinations. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.integer.linear.bb
Classes in dev.nm.solver.multivariate.constrained.integer.linear.bb that implement Minimizer Modifier and Type Class Description class
ILPBranchAndBoundMinimizer
This is a Branch-and-Bound algorithm that solves Integer Linear Programming problems. -
Uses of Minimizer in dev.nm.solver.multivariate.constrained.integer.linear.cuttingplane
Classes in dev.nm.solver.multivariate.constrained.integer.linear.cuttingplane that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim
Classes in dev.nm.solver.multivariate.geneticalgorithm.minimizer.deoptim that implement Minimizer Modifier and Type Class Description class
DEOptim
Differential Evolution (DE) is a global optimization method. -
Uses of Minimizer in dev.nm.solver.multivariate.geneticalgorithm.minimizer.local
Classes in dev.nm.solver.multivariate.geneticalgorithm.minimizer.local that implement Minimizer Modifier and Type Class Description class
GlobalSearchByLocalMinimizer
This minimizer is a global optimization method. -
Uses of Minimizer in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid
Classes in dev.nm.solver.multivariate.geneticalgorithm.minimizer.simplegrid that implement Minimizer Modifier and Type Class Description class
SimpleGridMinimizer
This minimizer is a simple global optimization method. -
Uses of Minimizer in dev.nm.solver.multivariate.unconstrained
Subinterfaces of Minimizer in dev.nm.solver.multivariate.unconstrained Modifier and Type Interface 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.Classes in dev.nm.solver.multivariate.unconstrained that implement Minimizer Modifier and Type Class Description class
DoubleBruteForceMinimizer
This implementation solves an unconstrained minimization problem by brute force search for all given possible values. -
Uses of Minimizer in dev.nm.solver.multivariate.unconstrained.annealing
Classes in dev.nm.solver.multivariate.unconstrained.annealing that implement Minimizer Modifier and Type Class Description class
GeneralizedSimulatedAnnealingMinimizer
Tsallis and Stariolo (1996) proposed this variant ofSimulatedAnnealingMinimizer
(SA).class
SimulatedAnnealingMinimizer
Simulated Annealing is a global optimization meta-heuristic that is inspired by annealing in metallurgy. -
Uses of Minimizer in dev.nm.solver.multivariate.unconstrained.c2
Subinterfaces of Minimizer in dev.nm.solver.multivariate.unconstrained.c2 Modifier and Type Interface Description interface
IterativeC2Minimizer
This is a minimizer that minimizes a twice continuously differentiable, multivariate function.Classes in dev.nm.solver.multivariate.unconstrained.c2 that implement Minimizer Modifier and Type Class Description class
NelderMeadMinimizer
The Nelder-Mead method is a nonlinear optimization technique, which is well-defined for twice differentiable and unimodal problems. -
Uses of Minimizer in dev.nm.solver.multivariate.unconstrained.c2.conjugatedirection
Classes in dev.nm.solver.multivariate.unconstrained.c2.conjugatedirection that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in dev.nm.solver.multivariate.unconstrained.c2.quasinewton
Classes in dev.nm.solver.multivariate.unconstrained.c2.quasinewton that implement Minimizer Modifier and Type Class 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.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. -
Uses of Minimizer in dev.nm.solver.multivariate.unconstrained.c2.steepestdescent
Classes in dev.nm.solver.multivariate.unconstrained.c2.steepestdescent that implement Minimizer Modifier and Type Class 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. -
Uses of Minimizer in tech.nmfin.portfoliooptimization.corvalan2005
Constructors in tech.nmfin.portfoliooptimization.corvalan2005 with parameters of type Minimizer Constructor Description Corvalan2005(Minimizer<? super ConstrainedOptimProblem,IterativeSolution<Vector>> minimizer, DiversificationMeasure diversificationMeasure, double deltaSigma, double deltaR)
Constructs an instance of the Corvalan model.
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