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Nonconvex constrained optimization
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Public Types | Public Member Functions | Static Public Member Functions | Public Attributes | List of all members
FunctionalProblem< Conf > Class Template Reference

#include <alpaqa/problem/functional-problem.hpp>

Detailed Description

template<Config Conf = DefaultConfig>
class alpaqa::FunctionalProblem< Conf >

Problem class that allows specifying the basic functions as C++ std::functions.

Definition at line 12 of file functional-problem.hpp.

+ Inheritance diagram for FunctionalProblem< Conf >:
+ Collaboration diagram for FunctionalProblem< Conf >:

Public Types

using Box = alpaqa::Box< config_t >
 

Public Member Functions

real_t eval_f (crvec x) const
 
void eval_grad_f (crvec x, rvec grad_fx) const
 
void eval_g (crvec x, rvec gx) const
 
void eval_grad_g_prod (crvec x, crvec y, rvec grad_gxy) const
 
void eval_grad_gi (crvec x, index_t i, rvec grad_gix) const
 
void eval_hess_L_prod (crvec x, crvec y, real_t scale, crvec v, rvec Hv) const
 
void eval_hess_ψ_prod (crvec x, crvec y, crvec Σ, real_t scale, crvec v, rvec Hv) const
 
void eval_jac_g (crvec x, rvec J_values) const
 
void eval_hess_L (crvec x, crvec y, real_t scale, rvec H_values) const
 
void eval_hess_ψ (crvec x, crvec y, crvec Σ, real_t scale, rvec H_values) const
 
bool provides_eval_grad_gi () const
 
bool provides_eval_jac_g () const
 
bool provides_eval_hess_L_prod () const
 
bool provides_eval_hess_L () const
 
bool provides_eval_hess_ψ_prod () const
 
bool provides_eval_hess_ψ () const
 
std::string get_name () const
 
 FunctionalProblem (const FunctionalProblem &)=default
 
FunctionalProblemoperator= (const FunctionalProblem &)=default
 
 FunctionalProblem (FunctionalProblem &&) noexcept=default
 
FunctionalProblemoperator= (FunctionalProblem &&) noexcept=default
 
void resize (length_t n, length_t m)
 Change the dimensions of the problem (number of decision variables and number of constaints).
 
length_t get_n () const
 Number of decision variables, n.
 
length_t get_m () const
 Number of constraints, m.
 
real_t eval_prox_grad_step (real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p) const
 
void eval_proj_diff_g (crvec z, rvec p) const
 
void eval_proj_multipliers (rvec y, real_t M) const
 
const Boxget_box_C () const
 
const Boxget_box_D () const
 
bool provides_get_box_C () const
 Only supported if the ℓ₁-regularization term is zero.
 

Static Public Member Functions

static real_t eval_proj_grad_step_box (const Box &C, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
 Projected gradient step for rectangular box C.
 
static void eval_prox_grad_step_box_l1_impl (const Box &C, const auto &λ, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
 Proximal gradient step for rectangular box C with ℓ₁-regularization.
 
static real_t eval_prox_grad_step_box_l1 (const Box &C, const auto &λ, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
 Proximal gradient step for rectangular box C with ℓ₁-regularization.
 
static real_t eval_prox_grad_step_box_l1_scal (const Box &C, real_t λ, real_t γ, crvec x, crvec grad_ψ, rvec x̂, rvec p)
 Proximal gradient step for rectangular box C with ℓ₁-regularization.
 
static void eval_proj_multipliers_box (const Box &D, rvec y, real_t M, index_t penalty_alm_split)
 

Public Attributes

std::function< real_t(crvec)> f
 
std::function< void(crvec, rvec)> grad_f
 
std::function< void(crvec, rvec)> g
 
std::function< void(crvec, crvec, rvec)> grad_g_prod
 
std::function< void(crvec, index_t, rvec)> grad_gi
 
std::function< void(crvec, rmat)> jac_g
 
std::function< void(crvec, crvec, real_t, crvec, rvec)> hess_L_prod
 
std::function< void(crvec, crvec, real_t, rmat)> hess_L
 
std::function< void(crvec, crvec, crvec, real_t, crvec, rvec)> hess_ψ_prod
 
std::function< void(crvec, crvec, crvec, real_t, rmat)> hess_ψ
 
length_t n
 Number of decision variables, dimension of x.
 
length_t m
 Number of constraints, dimension of g(x) and z.
 
Box C {this->n}
 Constraints of the decision variables, \( x \in C \).
 
Box D {this->m}
 Other constraints, \( g(x) \in D \).
 
vec l1_reg {}
 \( \ell_1 \) (1-norm) regularization parameter.
 
index_t penalty_alm_split = 0
 Components of the constraint function with indices below this number are handled using a quadratic penalty method rather than using an augmented Lagrangian method.
 

Member Typedef Documentation

◆ Box

template<Config Conf>
using Box = alpaqa::Box<config_t>
inherited

Definition at line 19 of file box-constr-problem.hpp.

Constructor & Destructor Documentation

◆ FunctionalProblem() [1/2]

template<Config Conf = DefaultConfig>
FunctionalProblem ( const FunctionalProblem< Conf > &  )
default

◆ FunctionalProblem() [2/2]

template<Config Conf = DefaultConfig>
FunctionalProblem ( FunctionalProblem< Conf > &&  )
defaultnoexcept

Member Function Documentation

◆ eval_f()

template<Config Conf = DefaultConfig>
real_t eval_f ( crvec  x) const
inline

Definition at line 29 of file functional-problem.hpp.

◆ eval_grad_f()

template<Config Conf = DefaultConfig>
void eval_grad_f ( crvec  x,
rvec  grad_fx 
) const
inline

Definition at line 30 of file functional-problem.hpp.

◆ eval_g()

template<Config Conf = DefaultConfig>
void eval_g ( crvec  x,
rvec  gx 
) const
inline

Definition at line 31 of file functional-problem.hpp.

◆ eval_grad_g_prod()

template<Config Conf = DefaultConfig>
void eval_grad_g_prod ( crvec  x,
crvec  y,
rvec  grad_gxy 
) const
inline

Definition at line 32 of file functional-problem.hpp.

◆ eval_grad_gi()

template<Config Conf = DefaultConfig>
void eval_grad_gi ( crvec  x,
index_t  i,
rvec  grad_gix 
) const
inline

Definition at line 33 of file functional-problem.hpp.

◆ eval_hess_L_prod()

template<Config Conf = DefaultConfig>
void eval_hess_L_prod ( crvec  x,
crvec  y,
real_t  scale,
crvec  v,
rvec  Hv 
) const
inline

Definition at line 34 of file functional-problem.hpp.

◆ eval_hess_ψ_prod()

template<Config Conf = DefaultConfig>
void eval_hess_ψ_prod ( crvec  x,
crvec  y,
crvec  Σ,
real_t  scale,
crvec  v,
rvec  Hv 
) const
inline

Definition at line 35 of file functional-problem.hpp.

◆ eval_jac_g()

template<Config Conf = DefaultConfig>
void eval_jac_g ( crvec  x,
rvec  J_values 
) const
inline

Definition at line 37 of file functional-problem.hpp.

◆ eval_hess_L()

template<Config Conf = DefaultConfig>
void eval_hess_L ( crvec  x,
crvec  y,
real_t  scale,
rvec  H_values 
) const
inline

Definition at line 41 of file functional-problem.hpp.

◆ eval_hess_ψ()

template<Config Conf = DefaultConfig>
void eval_hess_ψ ( crvec  x,
crvec  y,
crvec  Σ,
real_t  scale,
rvec  H_values 
) const
inline

Definition at line 45 of file functional-problem.hpp.

◆ provides_eval_grad_gi()

template<Config Conf = DefaultConfig>
bool provides_eval_grad_gi ( ) const
inline

◆ provides_eval_jac_g()

template<Config Conf = DefaultConfig>
bool provides_eval_jac_g ( ) const
inline

◆ provides_eval_hess_L_prod()

template<Config Conf = DefaultConfig>
bool provides_eval_hess_L_prod ( ) const
inline

◆ provides_eval_hess_L()

template<Config Conf = DefaultConfig>
bool provides_eval_hess_L ( ) const
inline

◆ provides_eval_hess_ψ_prod()

template<Config Conf = DefaultConfig>
bool provides_eval_hess_ψ_prod ( ) const
inline

◆ provides_eval_hess_ψ()

template<Config Conf = DefaultConfig>
bool provides_eval_hess_ψ ( ) const
inline

◆ get_name()

template<Config Conf = DefaultConfig>
std::string get_name ( ) const
inline
See also
TypeErasedProblem::get_name

Definition at line 64 of file functional-problem.hpp.

◆ operator=() [1/2]

template<Config Conf = DefaultConfig>
FunctionalProblem & operator= ( const FunctionalProblem< Conf > &  )
default

◆ operator=() [2/2]

template<Config Conf = DefaultConfig>
FunctionalProblem & operator= ( FunctionalProblem< Conf > &&  )
defaultnoexcept

◆ resize()

template<Config Conf>
void resize ( length_t  n,
length_t  m 
)
inlineinherited

Change the dimensions of the problem (number of decision variables and number of constaints).

Destructive: resizes and/or resets the members C, D, l1_reg and penalty_alm_split.

Parameters
nNumber of decision variables
mNumber of constraints

Definition at line 45 of file box-constr-problem.hpp.

◆ get_n()

template<Config Conf>
length_t get_n ( ) const
inlineinherited

Number of decision variables, n.

Definition at line 81 of file box-constr-problem.hpp.

◆ get_m()

template<Config Conf>
length_t get_m ( ) const
inlineinherited

Number of constraints, m.

Definition at line 83 of file box-constr-problem.hpp.

◆ eval_proj_grad_step_box()

template<Config Conf>
static real_t eval_proj_grad_step_box ( const Box C,
real_t  γ,
crvec  x,
crvec  grad_ψ,
rvec  ,
rvec  p 
)
inlinestaticinherited

Projected gradient step for rectangular box C.

\[ \begin{aligned} \hat x &= \Pi_C(x - \gamma\nabla\psi(x)) \\ p &= \hat x - x \\ &= \max(\underline x - x, \;\min(-\gamma\nabla\psi(x), \overline x - x) \end{aligned} \]

Definition at line 90 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step_box_l1_impl()

template<Config Conf>
static void eval_prox_grad_step_box_l1_impl ( const Box C,
const auto λ,
real_t  γ,
crvec  x,
crvec  grad_ψ,
rvec  ,
rvec  p 
)
inlinestaticinherited

Proximal gradient step for rectangular box C with ℓ₁-regularization.

\[ \begin{aligned} h(x) &= \|x\|_1 + \delta_C(x) \\ \hat x &= \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \\ &= -\max\big( x - \overline x, \;\min\big( x - \underline x, \;\min\big( \gamma(\nabla\psi(x) + \lambda), \;\max\big( \gamma(\nabla\psi(x) - \lambda), x \big) \big) \big) \big) \end{aligned} \]

Definition at line 113 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step_box_l1()

template<Config Conf>
static real_t eval_prox_grad_step_box_l1 ( const Box C,
const auto λ,
real_t  γ,
crvec  x,
crvec  grad_ψ,
rvec  ,
rvec  p 
)
inlinestaticinherited

Proximal gradient step for rectangular box C with ℓ₁-regularization.

\[ \begin{aligned} h(x) &= \|x\|_1 + \delta_C(x) \\ \hat x &= \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \\ &= -\max\big( x - \overline x, \;\min\big( x - \underline x, \;\min\big( \gamma(\nabla\psi(x) + \lambda), \;\max\big( \gamma(\nabla\psi(x) - \lambda), x \big) \big) \big) \big) \end{aligned} \]

Definition at line 122 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step_box_l1_scal()

template<Config Conf>
static real_t eval_prox_grad_step_box_l1_scal ( const Box C,
real_t  λ,
real_t  γ,
crvec  x,
crvec  grad_ψ,
rvec  ,
rvec  p 
)
inlinestaticinherited

Proximal gradient step for rectangular box C with ℓ₁-regularization.

\[ \begin{aligned} h(x) &= \|x\|_1 + \delta_C(x) \\ \hat x &= \prox_{\gamma h}(x - \gamma\nabla\psi(x)) \\ &= -\max\big( x - \overline x, \;\min\big( x - \underline x, \;\min\big( \gamma(\nabla\psi(x) + \lambda), \;\max\big( \gamma(\nabla\psi(x) - \lambda), x \big) \big) \big) \big) \end{aligned} \]

Definition at line 130 of file box-constr-problem.hpp.

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◆ eval_prox_grad_step()

template<Config Conf>
real_t eval_prox_grad_step ( real_t  γ,
crvec  x,
crvec  grad_ψ,
rvec  ,
rvec  p 
) const
inlineinherited
See also
TypeErasedProblem::eval_prox_grad_step

Definition at line 140 of file box-constr-problem.hpp.

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◆ eval_proj_diff_g()

template<Config Conf>
void eval_proj_diff_g ( crvec  z,
rvec  p 
) const
inlineinherited
See also
TypeErasedProblem::eval_proj_diff_g

Definition at line 150 of file box-constr-problem.hpp.

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◆ eval_proj_multipliers_box()

template<Config Conf>
static void eval_proj_multipliers_box ( const Box D,
rvec  y,
real_t  M,
index_t  penalty_alm_split 
)
inlinestaticinherited

Definition at line 152 of file box-constr-problem.hpp.

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◆ eval_proj_multipliers()

template<Config Conf>
void eval_proj_multipliers ( rvec  y,
real_t  M 
) const
inlineinherited
See also
TypeErasedProblem::eval_proj_multipliers

Definition at line 168 of file box-constr-problem.hpp.

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◆ get_box_C()

template<Config Conf>
const Box & get_box_C ( ) const
inlineinherited
See also
TypeErasedProblem::get_box_C

Definition at line 173 of file box-constr-problem.hpp.

◆ get_box_D()

template<Config Conf>
const Box & get_box_D ( ) const
inlineinherited
See also
TypeErasedProblem::get_box_D

Definition at line 175 of file box-constr-problem.hpp.

◆ provides_get_box_C()

template<Config Conf>
bool provides_get_box_C ( ) const
inlineinherited

Only supported if the ℓ₁-regularization term is zero.

See also
TypeErasedProblem::provides_get_box_C

Definition at line 179 of file box-constr-problem.hpp.

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Member Data Documentation

◆ f

template<Config Conf = DefaultConfig>
std::function<real_t(crvec)> f

Definition at line 17 of file functional-problem.hpp.

◆ grad_f

template<Config Conf = DefaultConfig>
std::function<void(crvec, rvec)> grad_f

Definition at line 18 of file functional-problem.hpp.

◆ g

template<Config Conf = DefaultConfig>
std::function<void(crvec, rvec)> g

Definition at line 19 of file functional-problem.hpp.

◆ grad_g_prod

template<Config Conf = DefaultConfig>
std::function<void(crvec, crvec, rvec)> grad_g_prod

Definition at line 20 of file functional-problem.hpp.

◆ grad_gi

template<Config Conf = DefaultConfig>
std::function<void(crvec, index_t, rvec)> grad_gi

Definition at line 21 of file functional-problem.hpp.

◆ jac_g

template<Config Conf = DefaultConfig>
std::function<void(crvec, rmat)> jac_g

Definition at line 22 of file functional-problem.hpp.

◆ hess_L_prod

template<Config Conf = DefaultConfig>
std::function<void(crvec, crvec, real_t, crvec, rvec)> hess_L_prod

Definition at line 23 of file functional-problem.hpp.

◆ hess_L

template<Config Conf = DefaultConfig>
std::function<void(crvec, crvec, real_t, rmat)> hess_L

Definition at line 24 of file functional-problem.hpp.

◆ hess_ψ_prod

template<Config Conf = DefaultConfig>
std::function<void(crvec, crvec, crvec, real_t, crvec, rvec)> hess_ψ_prod

Definition at line 25 of file functional-problem.hpp.

◆ hess_ψ

template<Config Conf = DefaultConfig>
std::function<void(crvec, crvec, crvec, real_t, rmat)> hess_ψ

Definition at line 26 of file functional-problem.hpp.

◆ n

template<Config Conf>
length_t n
inherited

Number of decision variables, dimension of x.

Examples
C++/CustomCppProblem/main.cpp.

Definition at line 22 of file box-constr-problem.hpp.

◆ m

template<Config Conf>
length_t m
inherited

Number of constraints, dimension of g(x) and z.

Examples
C++/CustomCppProblem/main.cpp.

Definition at line 24 of file box-constr-problem.hpp.

◆ C

template<Config Conf>
Box C {this->n}
inherited

Constraints of the decision variables, \( x \in C \).

Examples
C++/CasADi/Rosenbrock/main.cpp.

Definition at line 65 of file box-constr-problem.hpp.

◆ D

template<Config Conf>
Box D {this->m}
inherited

Other constraints, \( g(x) \in D \).

Definition at line 67 of file box-constr-problem.hpp.

◆ l1_reg

template<Config Conf>
vec l1_reg {}
inherited

\( \ell_1 \) (1-norm) regularization parameter.

Possible dimensions are: \( 0 \) (no regularization), \( 1 \) (a single scalar factor), or \( n \) (a different factor for each variable).

Definition at line 72 of file box-constr-problem.hpp.

◆ penalty_alm_split

template<Config Conf>
index_t penalty_alm_split = 0
inherited

Components of the constraint function with indices below this number are handled using a quadratic penalty method rather than using an augmented Lagrangian method.

Specifically, the Lagrange multipliers for these components (which determine the shifts in ALM) are kept at zero.

Definition at line 78 of file box-constr-problem.hpp.


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