Zobrazeno 1 - 10
of 13
pro vyhledávání: '"Songhai Deng"'
Publikováno v:
IEEE Access, Vol 8, Pp 85664-85674 (2020)
In this paper, a new spectral scaling memoryless Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is developed for solving large scale unconstrained optimization problems, where the scaling parameter is chosen so as to minimize all the eigenvalues o
Externí odkaz:
https://doaj.org/article/40a54bea29d94d7692ee1b291b187519
Publikováno v:
Journal of Applied Mathematics, Vol 2012 (2012)
A modified spectral PRP conjugate gradient method is presented for solving unconstrained optimization problems. The constructed search direction is proved to be a sufficiently descent direction of the objective function. With an Armijo-type line sear
Externí odkaz:
https://doaj.org/article/146397b3577c4b2aa3e6238bf14ccf7b
Publikováno v:
Soft Computing. 27:3805-3815
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::2fa4d20bda3b0a666ba35eec17aaa0af
https://doi.org/10.1007/s00500-022-07536-4
https://doi.org/10.1007/s00500-022-07536-4
Publikováno v:
IEEE Access, Vol 8, Pp 85664-85674 (2020)
In this paper, a new spectral scaling memoryless Broyden-Fletcher-Goldfarb-Shanno (BFGS) algorithm is developed for solving large scale unconstrained optimization problems, where the scaling parameter is chosen so as to minimize all the eigenvalues o
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::3f1ce987feb30558cc444a06399f3362
https://ieeexplore.ieee.org/document/9085988/
https://ieeexplore.ieee.org/document/9085988/
Publikováno v:
Discrete & Continuous Dynamical Systems - S. 13:1637-1652
In this paper, a two-product newsvendor problem is taken into consideration, where the demands of products are correlated random variables and the buyer is risk-averse. Some important qualitative properties of the constructed model are analyzed, part
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::08ad617834ecc6764b20d5097bf47d90
https://doi.org/10.3934/dcdss.2020096
https://doi.org/10.3934/dcdss.2020096
Publikováno v:
Journal of Industrial & Management Optimization. 13:1-20
In financial optimization, it is important to quantify the risk of structured financial products. This paper quantifies the risk of structured financial products by perceived risk measures based on a standard measure of risk, and then we construct th
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::48463e24e6e85e72e485b734ffe8c216
https://doi.org/10.3934/jimo.2018105
https://doi.org/10.3934/jimo.2018105
Autor:
Songhai Deng, Zhong Wan
Publikováno v:
Applied Numerical Mathematics. 92:70-81
In this paper, a three-term conjugate gradient algorithm is developed for solving large-scale unconstrained optimization problems. The search direction at each iteration of the algorithm is determined by rectifying the steepest descent direction with
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::e12d4682a004d4c3ba477558d16a675a
https://doi.org/10.1016/j.apnum.2015.01.008
https://doi.org/10.1016/j.apnum.2015.01.008
Autor:
Songhai Deng, Zhong Wan
Publikováno v:
Optimization. 64:2679-2691
In this article, we present an improved three-term conjugate gradient algorithm for large-scale unconstrained optimization. The search directions in the developed algorithm are proved to satisfy an approximate secant equation as well as the Dai-Liao
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::6df10224ef72c7855982659bf8e984e3
https://doi.org/10.1080/02331934.2014.984706
https://doi.org/10.1080/02331934.2014.984706
Publikováno v:
Journal of Optimization Theory and Applications. 157:820-842
In this paper, an improved spectral conjugate gradient algorithm is developed for solving nonconvex unconstrained optimization problems. Different from the existent methods, the spectral and conjugate parameters are chosen such that the obtained sear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::4b2f55d0651b33ff882dba703e76d269
https://doi.org/10.1007/s10957-012-0239-7
https://doi.org/10.1007/s10957-012-0239-7
Publikováno v:
J. Appl. Math.
Journal of Applied Mathematics, Vol 2012 (2012)
Journal of Applied Mathematics, Vol 2012 (2012)
A modified spectral PRP conjugate gradient method is presented for solving unconstrained optimization problems. The constructed search direction is proved to be a sufficiently descent direction of the objective function. With an Armijo-type line sear
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::36161cedad9bd37901cd85c07606544b
https://doi.org/10.1155/2012/641276
https://doi.org/10.1155/2012/641276