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 interfaceUnivariateMinimizerA univariate minimizer minimizes a univariate function.Classes in dev.nm.root.univariate that implement Minimizer Modifier and Type Class Description classGridSearchMinimizerThis 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 classBracketSearchMinimizerThis class provides implementation support for those univariate optimization algorithms that are based on bracketing.classBrentMinimizerBrent's algorithm is the preferred method for finding the minimum of a univariate function.classFibonaccMinimizerThe Fibonacci search is a dichotomous search where a bracketing interval is sub-divided by the Fibonacci ratio.classGoldenMinimizerThis 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 interfaceBoxMinimizer<P extends BoxOptimProblem,S extends MinimizationSolution<?>>A box minimizer solves aBoxOptimProblem.interfaceConstrainedMinimizer<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 classSubProblemMinimizerThis 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 classCSDPMinimizerImplements the CSDP algorithm for semidefinite programming problem with equality constraints.classHomogeneousPathFollowingMinimizerThis implementation solves a Semi-Definite Programming problem using the Homogeneous Self-Dual Path-Following algorithm.classPrimalDualPathFollowingMinimizerThe 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 classPrimalDualInteriorPointMinimizerSolves a Dual Second Order Conic Programming problem using the Primal Dual Interior Point algorithm.classPrimalDualInteriorPointMinimizer1The 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 interfaceLPSolver<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 interfaceLPSimplexSolver<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 classFerrisMangasarianWrightPhase2This implementation solves a canonical linear programming problem that does not need preprocessing its simplex table.classLPCanonicalSolverThis is an LP solver that solves a canonical LP problem in the following form.classLPRevisedSimplexSolverclassLPTwoPhaseSolverThis 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 interfaceQPMinimizerA 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 classQPDualActiveSetMinimizerThis implementation solves a Quadratic Programming problem using the dual active set algorithm.classQPPrimalActiveSetMinimizerThis 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 classQPbySOCPMinimizerWe first convert a QP problem to an equivalent SOCP problem and then solve it using an SOCP solver.classQPbySOCPMinimizer1A QP problem is first converted into an equivalent SOCP problemSOCPGeneralProblem1and then solve it using an SOCP solverPrimalDualInteriorPointMinimizer1. -
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 classBoxGeneralizedSimulatedAnnealingMinimizerThis 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 classPenaltyMethodMinimizerThe 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 classSQPActiveSetMinimizerSequential quadratic programming (SQP) is an iterative method for nonlinear optimization.classSQPActiveSetOnlyInequalityConstraintMinimizerThis 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 classSQPActiveSetOnlyEqualityConstraint1MinimizerThis implementation is a modified version of Algorithm 15.1 in the reference to solve a general constrained optimization problem with only equality constraints.classSQPActiveSetOnlyEqualityConstraint2MinimizerThis particular implementation ofSQPActiveSetOnlyEqualityConstraint1MinimizerusesSQPASEVariation2. -
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 interfaceIPMinimizer<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 classBruteForceIPMinimizerThis 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 classILPBranchAndBoundMinimizerThis 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 classGomoryMixedCutMinimizerThis cutting-plane implementation uses Gomory's mixed cut method.classGomoryPureCutMinimizerThis cutting-plane implementation uses Gomory's pure cut method for pure integer programming, in which all variables are integral.classSimplexCuttingPlaneMinimizerThe 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 classDEOptimDifferential 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 classGlobalSearchByLocalMinimizerThis 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 classSimpleGridMinimizerThis 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 interfaceIterativeMinimizer<P extends OptimProblem>This is an iterative multivariate minimizer.interfaceMultivariateMinimizer<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 classDoubleBruteForceMinimizerThis 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 classGeneralizedSimulatedAnnealingMinimizerTsallis and Stariolo (1996) proposed this variant ofSimulatedAnnealingMinimizer(SA).classSimulatedAnnealingMinimizerSimulated 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 interfaceIterativeC2MinimizerThis 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 classNelderMeadMinimizerThe 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 classConjugateGradientMinimizerA conjugate direction optimization method is performed by using sequential line search along directions that bear a strict mathematical relationship to one another.classFletcherReevesMinimizerThe Fletcher-Reeves method is a variant of the Conjugate-Gradient method.classPowellMinimizerPowell's algorithm, starting from an initial point, performs a series of line searches in one iteration.classZangwillMinimizerZangwill'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 classBFGSMinimizerThe Broyden-Fletcher-Goldfarb-Shanno method is a quasi-Newton method to solve unconstrained nonlinear optimization problems.classDFPMinimizerThe Davidon-Fletcher-Powell method is a quasi-Newton method to solve unconstrained nonlinear optimization problems.classHuangMinimizerHuang's updating formula is a family of formulas which encompasses the rank-one, DFP, BFGS as well as some other formulas.classMcCormickMinimizerDeprecated.the McCormick algorithm does not seem to work well; need further investigation; don't use it.classPearsonMinimizerThis is the Pearson method.classQuasiNewtonMinimizerThe Quasi-Newton methods in optimization are for finding local maxima and minima of functions.classRankOneMinimizerThe 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 classFirstOrderMinimizerThis implements the steepest descent line search using the first order expansion of the Taylor's series.protected static classGaussNewtonMinimizer.MySteepestDescentclassNewtonRaphsonMinimizerThe Newton-Raphson method is a second order steepest descent method that is based on the quadratic approximation of the Taylor series.classSteepestDescentMinimizerA 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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