class ConjGradient extends Error
The ConjGradient implements the Polak-Ribiere Conjugate Gradient (PR-CG) Algorithm
for solving Non-Linear Programming (NLP) problems. PR-CG determines a search
direction as a weighted combination of the steepest descent direction (-gradient)
and the previous direction. The weighting is set by the beta function, which for
this implementation used the Polak-Ribiere technique.
dir_k = -gradient (x) + beta * dir_k-1
maximize f(x) subject to g(x) <= 0 [ optionally g(x) == 0 ]
- Alphabetic
- By Inheritance
- ConjGradient
- Error
- AnyRef
- Any
- Hide All
- Show All
- Public
- Protected
Instance Constructors
- new ConjGradient(f: FunctionV2S, g: FunctionV2S = null, ineq: Boolean = true)
- f
the objective function to be maximized
- g
the constraint function to be satisfied, if any
- ineq
whether the constraint function must satisfy inequality or equality
Type Members
- type Pair = (VectorD, VectorD)
Value Members
- final def !=(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def ##: Int
- Definition Classes
- AnyRef → Any
- final def ==(arg0: Any): Boolean
- Definition Classes
- AnyRef → Any
- final def asInstanceOf[T0]: T0
- Definition Classes
- Any
- def beta(gr1: VectorD, gr2: VectorD): Double
Compute the beta function using the Polak-Ribiere (PR) technique.
Compute the beta function using the Polak-Ribiere (PR) technique. The function determines how much of the prior direction is mixed in with -gradient.
- gr1
the gradient at the current point
- gr2
the gradient at the next point
- def clone(): AnyRef
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.CloneNotSupportedException]) @native() @HotSpotIntrinsicCandidate()
- final def eq(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- def equals(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef → Any
- def fg(x: VectorD): Double
The objective function f re-scaled by a weighted penalty, if constrained.
The objective function f re-scaled by a weighted penalty, if constrained.
- x
the coordinate values of the current point
- final def flaw(method: String, message: String): Unit
- Definition Classes
- Error
- final def getClass(): Class[_ <: AnyRef]
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def hashCode(): Int
- Definition Classes
- AnyRef → Any
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def isInstanceOf[T0]: Boolean
- Definition Classes
- Any
- def lineSearch(x: VectorD, dir: VectorD): Double
Perform an inexact (e.g., 'WolfeLS' or exact (e.g., 'GoldenSectionLS' line search in the direction 'dir', returning the distance 'z' to move in that direction.
Perform an inexact (e.g., 'WolfeLS' or exact (e.g., 'GoldenSectionLS' line search in the direction 'dir', returning the distance 'z' to move in that direction.
- x
the current point
- dir
the direction to move in
- final def ne(arg0: AnyRef): Boolean
- Definition Classes
- AnyRef
- final def notify(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- final def notifyAll(): Unit
- Definition Classes
- AnyRef
- Annotations
- @native() @HotSpotIntrinsicCandidate()
- def setDerivatives(partials: Array[FunctionV2S]): Unit
Set the partial derivative functions.
Set the partial derivative functions. If these functions are available, they are more efficient and more accurate than estimating the values using difference quotients (the default approach).
- partials
the array of partial derivative functions
- def setSteepest(): Unit
Use the Steepest-Descent algorithm rather than the default PR-CG algorithm.
- def solve(x0: VectorD): VectorD
Solve the following Non-Linear Programming (NLP) problem using PR-CG: max { f(x) | g(x) <= 0 }.
Solve the following Non-Linear Programming (NLP) problem using PR-CG: max { f(x) | g(x) <= 0 }. To use explicit functions for gradient, replace 'gradient (fg, x._1 + s)' with 'gradientD (df, x._1 + s)'.
- x0
the starting point
- final def synchronized[T0](arg0: => T0): T0
- Definition Classes
- AnyRef
- def toString(): String
- Definition Classes
- AnyRef → Any
- final def wait(arg0: Long, arg1: Int): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
- final def wait(arg0: Long): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException]) @native()
- final def wait(): Unit
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.InterruptedException])
Deprecated Value Members
- def finalize(): Unit
- Attributes
- protected[lang]
- Definition Classes
- AnyRef
- Annotations
- @throws(classOf[java.lang.Throwable]) @Deprecated
- Deprecated