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

The class that implements an optimization algorithm based on Karpov's method. More...

#include <OptimumSolverKarpov.hpp>

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

 OptimumSolverKarpov ()
 Construct a default OptimumSolverKarpov instance.
 
 OptimumSolverKarpov (const OptimumSolverKarpov &other)
 Construct a copy of an OptimumSolverKarpov instance.
 
virtual ~OptimumSolverKarpov ()
 Destroy this OptimumSolverKarpov instance.
 
auto operator= (OptimumSolverKarpov other) -> OptimumSolverKarpov &
 Assign a copy of an OptimumSolverKarpov instance.
 
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 an optimization algorithm based on Karpov's method.

Member Function Documentation

◆ solve() [1/2]

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.

◆ solve() [2/2]

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.

◆ dxdp()

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: