scalation

maxima

package maxima

The maxima package contains classes, traits and objects for optimization to find maxima.

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Type Members

  1. class CheckLP extends Error

    This class checks the solution to Linear Programming (LP) problems.

  2. class ConjGradient extends Error

    Polak-Ribiere Conjugate Gradient (PR-CG) Algorithm for solving Non-Linear Programming (NLP) problems.

  3. class GoldenSectionLS extends AnyRef

    This class performs a line search on f(x) to find a maximal value for f.

  4. class Hungarian extends AnyRef

    This is an O(n^3) implementation of the Hungarian algorithm (or Kuhn-Munkres algorithm). Find the maximum cost set of pairings between m x-nodes (workers) and n y-nodes (jobs) such that each worker is assigned to one job and each job has at most one worker assigned. It solves the maximum-weighted bipartite graph matching problem.

  5. class IntegerProg extends AnyRef

    This class solves Integer Linear Programming (ILP) and Mixed Integer Linear Programming (MILP) problems recursively using the Simplex algorithm.

  6. class RevisedSimplex extends Error

    This class solves Linear Programming (LP) problems using the Revised Simplex Algorithm.

  7. class Simplex2P extends Error

    This class solves Linear Programming (LP) problems using a tableau based Simplex Algorithm.

Value Members

  1. object ConjGradientTest extends App

    This object is used to test the ConjGradient class.

  2. object GoldenSectionLSTest extends App

    This object is used to test the GoldenSectionLS class on scalar functions.

  3. object GoldenSectionLSTest2 extends App

    This object is used to test the GoldenSectionLS class on vector functions.

  4. object Hungarian extends App

    This object is used to test the Hungarian class.

  5. object IntegerProgTest extends App

    This object is used to test the IntegerProg class.

  6. object RevisedSimplexTest extends App

    Test the Revised Simplex Algorithm class with the following maximization problem: Maximize z = 2x_0 + 3x_1 + 4x_2 Subject to 3x_0 + 2x_1 + 1x_2 + 1y_3 + 0y_4 = 10 2x_0 + 5x_1 + 3x_2 + 0y_3 + 1y_4 = 15 where z is the objective variable, x are the decision variables and y are slack variables.

  7. object Simplex2PTest extends App

    This object is used to test the Simplex2P class.

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