Uses of Class
org.ojalgo.optimisation.GenericSolver
Packages that use GenericSolver
Package
Description
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Uses of GenericSolver in org.ojalgo.optimisation
Classes in org.ojalgo.optimisation with type parameters of type GenericSolverModifier and TypeClassDescriptionstatic class
GenericSolver.Builder<B extends GenericSolver.Builder<B,
S>, S extends GenericSolver> -
Uses of GenericSolver in org.ojalgo.optimisation.convex
Subclasses of GenericSolver in org.ojalgo.optimisation.convexModifier and TypeClassDescription(package private) class
(package private) class
(package private) class
class
ConvexSolver solves optimisation problems of the form:(package private) final class
Solves optimisation problems of the form:(package private) final class
Solves optimisation problems of the form:(package private) final class
Algorithm from: Solving quadratic programs to high precision using scaled iterative refinement
Mathematical Programming Computation (2019) 11:421–455 https://doi.org/10.1007/s12532-019-00154-6(package private) final class
Solves optimisation problems of the form:(package private) final class
Solves optimisation problems of the form: -
Uses of GenericSolver in org.ojalgo.optimisation.integer
Subclasses of GenericSolver in org.ojalgo.optimisation.integerModifier and TypeClassDescriptionfinal class
An alternative MIP solver using Gomory Mixed Integer (GMI) cuts – purely iterative with no branching.final class
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Uses of GenericSolver in org.ojalgo.optimisation.linear
Subclasses of GenericSolver in org.ojalgo.optimisation.linearModifier and TypeClassDescription(package private) final class
Requires all variables to have both lower and upper bounds.class
(package private) final class
First runs the dual algorithm (with a possibly modified objective function) to establish feasibility, and then the primal to reach optimality.(package private) final class
Requires the initial basis to be feasible (doesn't do a phase-1).(package private) class
Meant to replaceSimplexTableauSolver
.(package private) final class
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 constraints