#include <alpaqa/problem/box-constr-problem.hpp>
Implements common problem functions for minimization problems with box constraints.
Meant to be used as a base class for custom problem implementations. Supports optional \( \ell_1 \)-regularization.
Definition at line 16 of file box-constr-problem.hpp.
Public Types | |
using | Box = alpaqa::Box< config_t > |
Public Member Functions | |
BoxConstrProblem (length_t n, length_t m) | |
Create a problem with inactive boxes \( (-\infty, +\infty) \), with no \( \ell_1 \)-regularization, and all general constraints handled using ALM. | |
BoxConstrProblem (std::tuple< length_t, length_t > dims) | |
Create a problem with inactive boxes \( (-\infty, +\infty) \), with no \( \ell_1 \)-regularization, and all general constraints handled using ALM. | |
BoxConstrProblem (Box C, Box D, vec l1_reg=vec(0), index_t penalty_alm_split=0) | |
void | resize (length_t n, length_t m) |
Change the dimensions of the problem (number of decision variables and number of constaints). | |
BoxConstrProblem (const BoxConstrProblem &)=default | |
BoxConstrProblem & | operator= (const BoxConstrProblem &)=default |
BoxConstrProblem (BoxConstrProblem &&) noexcept=default | |
BoxConstrProblem & | operator= (BoxConstrProblem &&) noexcept=default |
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 Box & | get_box_C () const |
const Box & | get_box_D () const |
bool | provides_get_box_C () const |
Only supported if the ℓ₁-regularization term is zero. | |
index_t | eval_inactive_indices_res_lna (real_t γ, crvec x, crvec grad_ψ, rindexvec J) const |
void | check () const |
std::string | get_name () const |
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 | |
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. | |
using Box = alpaqa::Box<config_t> |
Definition at line 19 of file box-constr-problem.hpp.
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inline |
Create a problem with inactive boxes \( (-\infty, +\infty) \), with no \( \ell_1 \)-regularization, and all general constraints handled using ALM.
n | Number of decision variables |
m | Number of constraints |
Definition at line 29 of file box-constr-problem.hpp.
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inline |
Create a problem with inactive boxes \( (-\infty, +\infty) \), with no \( \ell_1 \)-regularization, and all general constraints handled using ALM.
dims | Number of variables and number of constraints. |
Definition at line 34 of file box-constr-problem.hpp.
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Definition at line 37 of file box-constr-problem.hpp.
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default |
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defaultnoexcept |
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.
n | Number of decision variables |
m | Number of constraints |
Definition at line 45 of file box-constr-problem.hpp.
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default |
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defaultnoexcept |
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Number of decision variables, n.
Definition at line 81 of file box-constr-problem.hpp.
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inline |
Number of constraints, m.
Definition at line 83 of file box-constr-problem.hpp.
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inlinestatic |
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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inlinestatic |
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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inlinestatic |
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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inlinestatic |
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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inline |
Definition at line 140 of file box-constr-problem.hpp.
Definition at line 168 of file box-constr-problem.hpp.
Definition at line 173 of file box-constr-problem.hpp.
Definition at line 175 of file box-constr-problem.hpp.
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Only supported if the ℓ₁-regularization term is zero.
Definition at line 179 of file box-constr-problem.hpp.
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inline |
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inline |
Definition at line 222 of file box-constr-problem.hpp.
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Definition at line 240 of file box-constr-problem.hpp.
length_t n |
Number of decision variables, dimension of x.
Definition at line 22 of file box-constr-problem.hpp.
length_t m |
Number of constraints, dimension of g(x) and z.
Definition at line 24 of file box-constr-problem.hpp.
Constraints of the decision variables, \( x \in C \).
Definition at line 65 of file box-constr-problem.hpp.
Other constraints, \( g(x) \in D \).
Definition at line 67 of file box-constr-problem.hpp.
vec l1_reg {} |
\( \ell_1 \) (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.
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.
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.