Module ojalgo
Package org.ojalgo.optimisation.linear
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Interface Summary Interface Description BasisRepresentation -
Class Summary Class Description DecomposedInverse Maintains an LU decomposition of the basis matrix for efficient solving of linear systems in the revised simplex method.DenseTableau DualSimplexSolver Requires all variables to have both lower and upper bounds.LinearSolver LinearSolver.Builder Compared toLinearSolver.StandardBuilderthis builder:
1) Accepts inequality constraints
2) Has relaxed the requiremnt on the RHS to be non-negative (both equalities and inequalities)LinearSolver.Configuration LinearSolver.ModelIntegration LinearSolver.NewIntegration An integration to a new/alternative/experimental LP-solver.LinearSolver.OldIntegration LinearStructure LP (simplex tableau) meta data.PhasedSimplexSolver First runs the dual algorithm (with a possibly modified objective function) to establish feasibility, and then the primal to reach optimality.PrimalSimplexSolver Requires the initial basis to be feasible (doesn't do a phase-1).ProductFormInverse ProductFormInverse.ArrayPool ProductFormInverse.ElementaryFactor RevisedStore SimplexSolver Meant to replaceSimplexTableauSolver.SimplexSolver.EnterInfo SimplexSolver.ExitInfo Exit fromSimplexStore.ColumnState.BASISto eitherSimplexStore.ColumnState.LOWERorSimplexStore.ColumnState.UPPER.SimplexSolver.IterDescr SimplexStore SimplexTableau SimplexTableauSolver Classic simplex tableau solver: Primal algorithm 2-phase All variables assumed >=0, and RHS required to be >=0 Variable bounds other than >=0 handled like constraintsSimplexTableauSolver.IterationPoint SparseTableau TableauCutGenerator -
Enum Summary Enum Description SimplexSolver.Direction SimplexStore.ColumnState