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

Inheritance diagram for OptimumSolverKarpov:

Collaboration diagram for OptimumSolverKarpov:

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

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

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

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`

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