public class GoldenMinimizer extends BracketSearchMinimizer
next
point.
The value of the function at this new point is calculated and compared to the current minimum.
A new bracketing interval is then chosen in the usual manner as in BracketSearchMinimizer
.
Choosing the golden section as the bisection ratio gives the fastest convergence among the algorithms that converge linearly.
This implementation guarantees that the next guess lies inside the bracketing interval.Modifier and Type | Class and Description |
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class |
GoldenMinimizer.Solution
This is the solution to a Golden section univariate optimization.
|
epsilon, maxIterations
Constructor and Description |
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GoldenMinimizer(double epsilon,
int maxIterations)
Construct a univariate minimizer using the Golden method.
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Modifier and Type | Method and Description |
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GoldenMinimizer.Solution |
solve(C2OptimProblem problem)
Solve an optimization problem, e.g.,
OptimProblem . |
solve
public GoldenMinimizer(double epsilon, int maxIterations)
epsilon
- a precision parameter: when a number |x| ≤ ε, it is considered 0maxIterations
- the maximum number of iterationspublic GoldenMinimizer.Solution solve(C2OptimProblem problem)
Optimizer
OptimProblem
.problem
- an optimization problemCopyright © 2010-2020 NM FinTech Ltd.. All Rights Reserved.