scalation.minima

MinimizerLP

trait MinimizerLP extends Error

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

minimize c x subject to a x <= b, x >= 0

where a is the constraint matrix b is the limit/RHS vector c is the cost vector

Classes mixing in this trait must implement an objective function (objF) an iterative method (solve) that searches for improved solutions (x-vectors with lower objective function values.

Linear Supertypes
Error, AnyRef, Any
Known Subclasses
Ordering
  1. Alphabetic
  2. By inheritance
Inherited
  1. MinimizerLP
  2. Error
  3. AnyRef
  4. Any
  1. Hide All
  2. Show all
Learn more about member selection
Visibility
  1. Public
  2. All

Abstract Value Members

  1. abstract val checker: CheckLP

    Attributes
    protected
  2. abstract def objF(x: VectorD): Double

    The objective function, e.

    The objective function, e.g., c x.

    x

    the coordinate values of the current point

  3. abstract def solve(): VectorD

    Run the simplex algorithm starting from an initial BFS and iteratively find a non-basic variable to replace a variable in the current basis so long as the objective function improves.

    Run the simplex algorithm starting from an initial BFS and iteratively find a non-basic variable to replace a variable in the current basis so long as the objective function improves. Return the optimal solution vector.

Concrete Value Members

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

    Definition Classes
    AnyRef → Any
  2. final def ##(): Int

    Definition Classes
    AnyRef → Any
  3. final def ==(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  4. val EPSILON: Double

    Attributes
    protected
  5. final def asInstanceOf[T0]: T0

    Definition Classes
    Any
  6. def check(x: VectorD, y: VectorD, f: Double): Boolean

    Determine whether the current solution is correct.

    Determine whether the current solution is correct.

    x

    the primal solution vector x

    y

    the dual solution vector y

    f

    the minimum value of the objective function

  7. def clone(): AnyRef

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  8. final def eq(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  9. def equals(arg0: Any): Boolean

    Definition Classes
    AnyRef → Any
  10. def finalize(): Unit

    Attributes
    protected[java.lang]
    Definition Classes
    AnyRef
    Annotations
    @throws( classOf[java.lang.Throwable] )
  11. def flaw(method: String, message: String): Unit

    Show the flaw by printing the error message.

    Show the flaw by printing the error message.

    method

    the method where the error occurred

    message

    the error message

    Definition Classes
    Error
  12. final def getClass(): Class[_]

    Definition Classes
    AnyRef → Any
  13. def hashCode(): Int

    Definition Classes
    AnyRef → Any
  14. final def isInstanceOf[T0]: Boolean

    Definition Classes
    Any
  15. final def ne(arg0: AnyRef): Boolean

    Definition Classes
    AnyRef
  16. final def notify(): Unit

    Definition Classes
    AnyRef
  17. final def notifyAll(): Unit

    Definition Classes
    AnyRef
  18. final def synchronized[T0](arg0: ⇒ T0): T0

    Definition Classes
    AnyRef
  19. def toString(): String

    Definition Classes
    AnyRef → Any
  20. final def wait(): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  21. final def wait(arg0: Long, arg1: Int): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )
  22. final def wait(arg0: Long): Unit

    Definition Classes
    AnyRef
    Annotations
    @throws( ... )

Inherited from Error

Inherited from AnyRef

Inherited from Any

Ungrouped