Modifier and Type | Interface and Description |
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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.
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Modifier and Type | Class and Description |
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class |
BruteForceIPMinimizer
This implementation solves an integral constrained minimization problem by
brute force search for all possible integer combinations.
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Modifier and Type | Class and Description |
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class |
ILPBranchAndBoundMinimizer
This is a Branch-and-Bound algorithm that solves Integer Linear Programming problems.
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Modifier and Type | Class and Description |
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class |
DEOptim
Differential Evolution (DE) is a global optimization method.
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Modifier and Type | Class and Description |
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class |
GlobalSearchByLocalMinimizer
This minimizer is a global optimization method.
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Modifier and Type | Class and Description |
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class |
SimpleGridMinimizer
This minimizer is a simple global optimization method.
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Modifier and Type | Interface and Description |
---|---|
interface |
IterativeMinimizer<P extends OptimProblem>
This is an iterative multivariate minimizer.
|
Modifier and Type | Class and Description |
---|---|
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.
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Modifier and Type | Interface and Description |
---|---|
interface |
IterativeC2Minimizer
This is a minimizer that minimizes a twice continuously differentiable, multivariate function.
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Modifier and Type | Class and Description |
---|---|
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 | 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.
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