Lifted stationary points of sparse optimization with complementarity constraints
We aim to compute lifted stationary points of a sparse optimization problem ( P 0 ) with complementarity constraints. We define a continuous relaxation problem ( R ν ) that has the same global minimizers and optimal value with problem ( P 0 ). Problem ( R ν ) is a mathematical program with complemen...
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| Veröffentlicht in: | Computational optimization and applications Jg. 84; H. 3; S. 973 - 1003 |
|---|---|
| Hauptverfasser: | , |
| Format: | Journal Article |
| Sprache: | Englisch |
| Veröffentlicht: |
New York
Springer US
01.04.2023
Springer Nature B.V |
| Schlagworte: | |
| ISSN: | 0926-6003, 1573-2894 |
| Online-Zugang: | Volltext |
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| Zusammenfassung: | We aim to compute lifted stationary points of a sparse optimization problem (
P
0
) with complementarity constraints. We define a continuous relaxation problem (
R
ν
) that has the same global minimizers and optimal value with problem (
P
0
). Problem (
R
ν
) is a mathematical program with complementarity constraints (MPCC) and a difference-of-convex objective function. We define MPCC lifted-stationarity of (
R
ν
) and show that it is weaker than directional stationarity, but stronger than Clarke stationarity for local optimality. Moreover, we propose an approximation method to solve (
R
ν
) and an augmented Lagrangian method to solve its subproblem (
R
ν
,
σ
), which relaxes the equality constraint in (
R
ν
) with a tolerance
σ
. We prove the convergence of our algorithm to an MPCC lifted-stationary point of problem (
R
ν
) and use a sparse optimization problem with vertical linear complementarity constraints to demonstrate the efficiency of our algorithm on finding sparse solutions in practice. |
|---|---|
| Bibliographie: | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 |
| ISSN: | 0926-6003 1573-2894 |
| DOI: | 10.1007/s10589-022-00444-1 |