| bibtype |
J -
Journal Article
|
| ARLID |
0489264 |
| utime |
20240103215946.8 |
| mtime |
20180502235959.9 |
| SCOPUS |
85042236326 |
| WOS |
000431036800007 |
| DOI |
10.1007/s10589-018-9985-2 |
| title
(primary) (eng) |
Convergence of a Scholtes-type regularization method for cardinality-constrained optimization problems with an application in sparse robust portfolio optimization |
| specification |
| page_count |
28 s. |
| media_type |
P |
|
| serial |
| ARLID |
cav_un_epca*0252565 |
| ISSN |
0926-6003 |
| title
|
Computational Optimization and Applications |
| volume_id |
70 |
| volume |
2 (2018) |
| page_num |
503-530 |
| publisher |
|
|
| keyword |
Cardinality constraints |
| keyword |
Regularization method |
| keyword |
Scholtes regularization |
| keyword |
Strong stationarity |
| keyword |
Sparse portfolio optimization |
| keyword |
Robust portfolio optimization |
| author
(primary) |
| ARLID |
cav_un_auth*0280972 |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept (eng) |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department (eng) |
MTR |
| full_dept |
Department of Decision Making Theory |
| name1 |
Branda |
| name2 |
Martin |
| institution |
UTIA-B |
| country |
CZ |
| garant |
K |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0302028 |
| name1 |
Bucher |
| name2 |
M. |
| country |
DE |
|
| author
|
| ARLID |
cav_un_auth*0220207 |
| full_dept (cz) |
Matematická teorie rozhodování |
| full_dept |
Department of Decision Making Theory |
| department (cz) |
MTR |
| department |
MTR |
| full_dept |
Department of Decision Making Theory |
| name1 |
Červinka |
| name2 |
Michal |
| institution |
UTIA-B |
| garant |
S |
| fullinstit |
Ústav teorie informace a automatizace AV ČR, v. v. i. |
|
| author
|
| ARLID |
cav_un_auth*0332700 |
| name1 |
Schwartz |
| name2 |
A. |
| country |
DE |
| garant |
S |
|
| source |
|
| cas_special |
| project |
| ARLID |
cav_un_auth*0321507 |
| project_id |
GA15-00735S |
| agency |
GA ČR |
|
| abstract
(eng) |
We consider general nonlinear programming problems with cardinality constraints. By relaxing the binary variables which appear in the natural mixed-integer programming formulation, we obtain an almost equivalent nonlinear programming problem, which is thus still difficult to solve. Therefore, we apply a Scholtes-type regularization method to obtain a sequence of easier to solve problems and investigate the convergence of the obtained KKT points. We show that such a sequence converges to an S-stationary point, which corresponds to a local minimizer of the original\nproblem under the assumption of convexity. Additionally, we consider portfolio optimization problems where we minimize a risk measure under a cardinality constraint on the portfolio. Various risk measures are considered, in particular Value-at-Risk and Conditional Value-at-Risk under normal distribution of returns and their robust counterparts under moment conditions. For these investment problems formulated as nonlinear programming problems with cardinality constraints we perform a numerical study on a large number of simulated instances taken from the literature and illuminate the computational performance of the Scholtes-type regularization method in comparison to other considered solution approaches: a mixed-integer solver, a direct continuous reformulation solver and the Kanzow-Schwartz regularization method, which has already been applied to Markowitz portfolio problems. |
| result_subspec |
WOS |
| RIV |
BB |
| FORD0 |
10000 |
| FORD1 |
10100 |
| FORD2 |
10103 |
| reportyear |
2019 |
| num_of_auth |
4 |
| mrcbC52 |
4 A hod 4ah 20231122143147.7 |
| inst_support |
RVO:67985556 |
| permalink |
http://hdl.handle.net/11104/0283708 |
| mrcbC64 |
1 Department of Decision Making Theory UTIA-B 10102 MATHEMATICS, APPLIED |
| confidential |
S |
| mrcbC86 |
1 Article Operations Research Management Science|Mathematics Applied |
| mrcbT16-e |
MATHEMATICS.APPLIED|OPERATIONSRESEARCH&MANAGEMENTSCIENCE |
| mrcbT16-f |
2.064 |
| mrcbT16-g |
0.468 |
| mrcbT16-h |
7.4 |
| mrcbT16-i |
0.00626 |
| mrcbT16-j |
1.078 |
| mrcbT16-k |
2485 |
| mrcbT16-s |
0.997 |
| mrcbT16-5 |
1.753 |
| mrcbT16-6 |
94 |
| mrcbT16-7 |
Q1 |
| mrcbT16-B |
83.341 |
| mrcbT16-C |
70.1 |
| mrcbT16-D |
Q1 |
| mrcbT16-E |
Q2 |
| mrcbT16-M |
0.93 |
| mrcbT16-N |
Q2 |
| mrcbT16-P |
82.48 |
| arlyear |
2018 |
| mrcbTft |
\nSoubory v repozitáři: branda-0489264.pdf |
| mrcbU14 |
85042236326 SCOPUS |
| mrcbU24 |
PUBMED |
| mrcbU34 |
000431036800007 WOS |
| mrcbU63 |
cav_un_epca*0252565 Computational Optimization and Applications 0926-6003 1573-2894 Roč. 70 č. 2 2018 503 530 Springer |
|