Name | Description | Type | Package | Framework |
BFGSMinimizer | The Broyden-Fletcher-Goldfarb-Shanno method is a quasi-Newton method to solve unconstrained nonlinear optimization problems. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
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 | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.conjugatedirection | SuanShu |
DFPMinimizer | The Davidon-Fletcher-Powell method is a quasi-Newton method to solve unconstrained nonlinear optimization problems. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
FirstOrderMinimizer | This implements the steepest descent line search using the first order expansion of the Taylor's series. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
FirstOrderMinimizer .Method | the available methods to do line searchThe line search is done analytically. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
FletcherLineSearch | This is Fletcher's inexact line search method. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.linesearch | SuanShu |
FletcherReevesMinimizer | The Fletcher-Reeves method is a variant of the Conjugate-Gradient method. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.conjugatedirection | SuanShu |
GaussNewtonMinimizer | The Gauss-Newton method is a steepest descent method to minimize a real vector function in the form: f(x) = [f_1(x), f_2(x), . | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
GaussNewtonMinimizer .MySteepestDescent | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu | |
HuangMinimizer | Huang's updating formula is a family of formulas which encompasses the rank-one, DFP, BFGS as well as some other formulas. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
IterativeC2Maximizer | A maximization problem is simply minimizing the negative of the objective function. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2 | SuanShu |
IterativeC2Maximizer .Solution | Interface | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2 | SuanShu | |
IterativeC2Minimizer | This is a minimizer that minimizes a twice continuously differentiable, multivariate function. | Interface | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2 | SuanShu |
LineSearch | A line search is often used in another minimization algorithm to improve the current solution in one iteration step. | Interface | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.linesearch | SuanShu |
LineSearch .Solution | This is the solution to a line search minimization. | Interface | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.linesearch | SuanShu |
McCormickMinimizer | This is the McCormick method. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
NelderMeadMinimizer | The Nelder-Mead method is a nonlinear optimization technique, which is well-defined for twice differentiable and unimodal problems. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2 | SuanShu |
NewtonRaphsonMinimizer | The Newton-Raphson method is a second order steepest descent method that is based on the quadratic approximation of the Taylor series. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
PearsonMinimizer | This is the Pearson method. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
PowellMinimizer | Powell's algorithm, starting from an initial point, performs a series of line searches in one iteration. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.conjugatedirection | SuanShu |
QuasiNewtonMinimizer | The Quasi-Newton methods in optimization are for finding local maxima and minima of functions. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
RankOneMinimizer | The Rank One method is a quasi-Newton method to solve unconstrained nonlinear optimization problems. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.quasinewton | SuanShu |
SteepestDescentMinimizer | A steepest descent algorithm finds the minimum by moving along the negative of the steepest gradient direction. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.steepestdescent | SuanShu |
ZangwillMinimizer | Zangwill's algorithm is an improved version of Powell's algorithm. | Class | com.numericalmethod.suanshu.optimization.multivariate.unconstrained.c2.conjugatedirection | SuanShu |