scalation.minima

Minimizer

trait Minimizer extends AnyRef

This trait sets the pattern for optimization algorithms for solving Non-Linear Programming (NLP) problems of the form:

minimize f(x) subject to g(x) <= 0 [ optionally g(x) == 0 ]

where f is the objective function to be minimized g is the constraint function to be satisfied, if any

Classes mixing in this trait must implement a function (fg) that rolls the constraints into the objective functions as penalties for constraint violation, a one-dimensional Line Search (LS) algorithm (lineSearch) and an iterative method (solve) that searches for improved solutions (x-vectors with lower objective function values (f(x)).

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Abstract Value Members

  1. abstract def lineSearch(x: VectorD, dir: VectorD, step: Double = STEP): Double

    Perform an exact (e.

    Perform an exact (e.g., GoldenSectionLS) or inexact (e.g., WolfeLS) line search. Search in direction 'dir', returning the distance 'z' to move in that direction.

    x

    the current point

    dir

    the direction to move in

    step

    the initial step size

  2. abstract def solve(x0: VectorD, step: Double = STEP, toler: Double = EPSILON): VectorD

    Solve the Non-Linear Programming (NLP) problem by starting at 'x0' and iteratively moving down in the search space to a minimal point.

    Solve the Non-Linear Programming (NLP) problem by starting at 'x0' and iteratively moving down in the search space to a minimal point.

    x0

    the starting point

    step

    the initial step size

    toler

    the tolerance

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  1. final def !=(arg0: Any): Boolean

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  2. final def ##(): Int

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  4. val EPSILON: Double

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  5. val MAX_ITER: Int

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  6. val STEP: Double

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  10. def equals(arg0: Any): Boolean

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  11. def fg(x: VectorD): Double

    The objective function f plus a weighted penalty based on the constraint function g.

    The objective function f plus a weighted penalty based on the constraint function g. Override for constrained optimization and ignore for unconstrained optimization.

    x

    the coordinate values of the current point

  12. def finalize(): Unit

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