This class checks the solution to Linear Programming (LP) problems.
Polak-Ribiere Conjugate Gradient (PR-CG) Algorithm for solving Non-Linear Programming (NLP) problems.
This class performs a line search on f(x) to find a maximal value for f.
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.
This class solves Integer Linear Programming (ILP) and Mixed Integer Linear Programming (MILP) problems recursively using the Simplex algorithm.
This class solves Linear Programming (LP) problems using the Revised Simplex Algorithm.
This class solves Linear Programming (LP) problems using a tableau based Simplex Algorithm.
This object is used to test the ConjGradient class.
This object is used to test the GoldenSectionLS class on scalar functions.
This object is used to test the GoldenSectionLS class on vector functions.
This object is used to test the Hungarian class.
This object is used to test the IntegerProg class.
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.
This object is used to test the Simplex2P class.
The maxima package contains classes, traits and objects for optimization to find maxima.