Reaktoro
A unified framework for modeling chemically reactive systems
OptimumSolverSimplex Class Reference

The class that implements the simplex algorithm for linear programming problems. More...

#include <OptimumSolverSimplex.hpp>

Inheritance diagram for OptimumSolverSimplex:
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Collaboration diagram for OptimumSolverSimplex:
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Public Member Functions

 OptimumSolverSimplex ()
 Construct a default OptimumSolverSimplex instance.
 
 OptimumSolverSimplex (const OptimumSolverSimplex &other)
 Construct a copy of an OptimumSolverSimplex instance.
 
virtual ~OptimumSolverSimplex ()
 Destroy this OptimumSolverSimplex instance.
 
auto operator= (OptimumSolverSimplex other) -> OptimumSolverSimplex &
 Assign a copy of an OptimumSolverSimplex instance.
 
auto feasible (const OptimumProblem &problem, OptimumState &state, const OptimumOptions &options) -> OptimumResult
 Find a feasible point for the linear optimisation problem. More...
 
auto simplex (const OptimumProblem &problem, OptimumState &state, const OptimumOptions &options) -> OptimumResult
 Solve the linear optimisation problem with starting from a feasible point. More...
 
virtual auto solve (const OptimumProblem &problem, OptimumState &state) -> OptimumResult
 Solve the linear optimisation problem by finding a feasible point and then applying a simplex algorithm. More...
 
virtual auto solve (const OptimumProblem &problem, OptimumState &state, const OptimumOptions &options) -> OptimumResult
 Solve the linear optimisation problem by finding a feasible point and then applying a simplex algorithm. More...
 
virtual auto dxdp (VectorConstRef dgdp, VectorConstRef dbdp) -> Vector
 Return the sensitivity dx/dp of the solution x with respect to a vector of parameters p. More...
 
virtual auto clone () const -> OptimumSolverBase *
 Return a clone of this instance.
 
- Public Member Functions inherited from OptimumSolverBase
virtual ~OptimumSolverBase ()=0
 Pure virtual destructor.
 

Detailed Description

The class that implements the simplex algorithm for linear programming problems.

Member Function Documentation

auto feasible ( const OptimumProblem problem,
OptimumState state,
const OptimumOptions options 
) -> OptimumResult

Find a feasible point for the linear optimisation problem.

Parameters
problemThe definition of the linear optimisation problem
state[in,out]The initial guess and the final state of the optimisation approximation
optionsThe options for the optimisation calculation
auto simplex ( const OptimumProblem problem,
OptimumState state,
const OptimumOptions options 
) -> OptimumResult

Solve the linear optimisation problem with starting from a feasible point.

Parameters
problemThe definition of the linear optimisation problem
state[in,out]The initial guess and the final state of the optimisation approximation
optionsThe options for the optimisation calculation
auto solve ( const OptimumProblem problem,
OptimumState state 
) -> OptimumResult
virtual

Solve the linear optimisation problem by finding a feasible point and then applying a simplex algorithm.

Parameters
problemThe definition of the linear optimisation problem
state[in,out]The initial guess and the final state of the optimisation approximation

Implements OptimumSolverBase.

auto solve ( const OptimumProblem problem,
OptimumState state,
const OptimumOptions options 
) -> OptimumResult
virtual

Solve the linear optimisation problem by finding a feasible point and then applying a simplex algorithm.

Parameters
problemThe definition of the linear optimisation problem
state[in,out]The initial guess and the final state of the optimisation approximation
optionsThe options for the optimisation calculation

Implements OptimumSolverBase.

auto dxdp ( VectorConstRef  dgdp,
VectorConstRef  dbdp 
) -> Vector
virtual

Return the sensitivity dx/dp of the solution x with respect to a vector of parameters p.

Parameters
dgdpThe derivatives dg/dp of the objective gradient grad(f) with respect to the parameters p
dbdpThe derivatives db/dp of the vector b with respect to the parameters p

Implements OptimumSolverBase.


The documentation for this class was generated from the following files: