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.

## ◆ 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
 problem The 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
 problem The definition of the linear optimisation problem state[in,out] The initial guess and the final state of the optimisation approximation options The 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
 dgdp The derivatives dg/dp of the objective gradient grad(f) with respect to the parameters p dbdp The 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: