scalation/scalation/scalation.optimization/WolfeLS

WolfeLS

scalation.optimization.WolfeLS

class WolfeLS(f: FunctionS2S, c1: Double, c2: Double) extends LineSearch

The WolfeLS class performs an inexact line search on f to find a point x that exhibits (1) SDC: sufficient decrease (f(x) enough less that f(0)) and (2) CC: the slope at x is less steep than the slope at 0. That is, the line search looks for a value for x satisfying the two Wolfe conditions.

f(x) <= f(0) + c1 * f'(0) * x Wolfe condition 1 (Armijo condition) |f'(x)| <= |c2 * f'(0)| Wolfe condition 2 (Strong version) f'(x) >= c2 * f'(0) Wolfe condition 2 (Weak version, more robust)

It works on scalar functions (@see wolfeLSTest). If starting with a vector function f(x), simply defines a new function fl(a) = x0 + direction * a (@see wolfeLSTest2).

Value parameters

c1: constant for sufficient decrease (Wolfe condition 1)
c2: constant for curvature/slope constraint (Wolfe condition 2)
f: the scalar objective function to minimize

Attributes

Graph
Supertypes: trait LineSearch

class Object

trait Matchable

class Any

Members list

Value members

Concrete methods

Perform an inexact Line Search (LS) on the function f to find a point x that satisfies the Wolfe Conditions 1 and 2.

Value parameters

lo0: the lower bound for x
x0: the current point

Attributes

Perform an inexact Line Search (LS) on the function f to find a point x that satisfies the Wolfe Conditions 1 and 2. A Bisection Method for the Wolfe Conditions

Value parameters

lo0: the lower bound for x (defaults to 0)
weak: whether to use the weak (true) or strong (false) Wolfe conditions
x0: the current point (defaults to 1)

Attributes

See also: sites.math.washington.edu/~burke/crs/408/notes/nlp/line.pdf

Perform an inexact Line Search (LS) using the Wolfe approach with defaults.

Value parameters

step: the initial step size

Attributes

Inherited fields

Attributes

Inherited from:: LineSearch

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