Zobrazeno 1 - 10
of 26
pro vyhledávání: '"Rujun Jiang"'
Autor:
Rujun Jiang, Xudong Li
Publikováno v:
Mathematics of Operations Research. 47:3025-3050
In this paper, we study the local variational geometry of the optimal solution set of the trust region subproblem (TRS), which minimizes a general, possibly nonconvex, quadratic function over the unit ball. Specifically, we demonstrate that a Hölder
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2715a44c89ad3216415aaf0c3052f2cd
https://doi.org/10.1287/moor.2021.1243
https://doi.org/10.1287/moor.2021.1243
Publikováno v:
IFAC-PapersOnLine. 55:116-121
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b67106cb2ff710e906d7f6e8753d0339
https://doi.org/10.1016/j.ifacol.2022.09.010
https://doi.org/10.1016/j.ifacol.2022.09.010
Autor:
Duan Li, Rujun Jiang
Publikováno v:
Mathematics of Operations Research.
The extended trust region subproblem (ETRS) of minimizing a quadratic objective over the unit ball with additional linear constraints has attracted a lot of attention in the last few years because of its theoretical significance and wide spectra of a
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::a7ddf4d1b47aae518170bf2c1b5b367f
https://doi.org/10.1287/moor.2022.1305
https://doi.org/10.1287/moor.2022.1305
Publikováno v:
INFORMS Journal on Computing. 33:180-197
In this paper, we consider the so-called worst-case linear optimization (WCLO) with uncertainties on the right-hand side of the constraints. Such a problem often arises in applications such as in systemic risk estimation in finance and stochastic opt
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6adbc2bd608bfc26c432316a00d62352
https://doi.org/10.1287/ijoc.2019.0941
https://doi.org/10.1287/ijoc.2019.0941
Autor:
Duan Li, Rujun Jiang
Publikováno v:
SIAM Journal on Optimization. 30:915-932
In this paper, we provide the first provable linear-time (in the number of non-zero entries of the input) algorithm for approximately solving the generalized trust region subproblem (GTRS) of minimizing a quadratic function over a quadratic constrain
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f84b64bc9f19ec071f8b399128c2037
https://doi.org/10.1137/18m1215165
https://doi.org/10.1137/18m1215165
Autor:
Duan Li, Rujun Jiang
Publikováno v:
Journal of Global Optimization. 75:461-494
In this paper, we present new convex relaxations for nonconvex quadratically constrained quadratic programming (QCQP) problems. While recent research has focused on strengthening convex relaxations of QCQP using the reformulation-linearization techni
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::25fe6b2117bd58f1b2332b5be8e23cda
https://doi.org/10.1007/s10898-019-00793-y
https://doi.org/10.1007/s10898-019-00793-y
Publikováno v:
European Journal of Operational Research. 274:824-836
In production planning and resource allocation problems, we often encounter a situation where a constraint can be relaxed or removed if new resources are added. Such constraints are termed on–off constraints. We study the quadratic programming prob
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::37ca6129e1d57796e01eb726ceec5de1
https://doi.org/10.1016/j.ejor.2018.09.028
https://doi.org/10.1016/j.ejor.2018.09.028
Autor:
Duan Li, Rujun Jiang
Publikováno v:
SIAM Journal on Optimization. 29:1603-1633
We present a new solution framework to solve the generalized trust region subproblem (GTRS) of minimizing a quadratic objective over a quadratic constraint. More specifically, we derive a convex quadratic reformulation (CQR) via minimizing a linear o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::f42a18b0c6ee8e091aca2edc7103dfb1
https://doi.org/10.1137/18m1174313
https://doi.org/10.1137/18m1174313
Publikováno v:
INFORMS Journal on Computing. 30:454-471
In this paper, we investigate a portfolio optimization methodology using nonparametric value at risk (VaR). In particular, we adopt kernel VaR and quadratic VaR as risk measures. As the resulting models are nonconvex and nonsmooth optimization proble
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::b747d989ed169cb7ece3ebec8c1a9de0
https://doi.org/10.1287/ijoc.2017.0793
https://doi.org/10.1287/ijoc.2017.0793
Publikováno v:
Mathematical Programming. 169:531-563
We investigate in this paper the generalized trust region subproblem (GTRS) of minimizing a general quadratic objective function subject to a general quadratic inequality constraint. By applying a simultaneous block diagonalization approach, we obtai
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3ea40b3183eaee67b09fc11d122329ab
https://doi.org/10.1007/s10107-017-1145-4
https://doi.org/10.1007/s10107-017-1145-4