Railway timetabling using Lagrangian relaxation
U Brännlund, PO Lindberg, A Nou… - Transportation …, 1998 - pubsonline.informs.org
We present a novel optimization approach for the timetabling problem of a railway company,
ie, scheduling of a set of trains to obtain a profit maximizing timetable, while not violating …
ie, scheduling of a set of trains to obtain a profit maximizing timetable, while not violating …
Survey of bundle methods for nonsmooth optimization
M Mäkelä - Optimization methods and software, 2002 - Taylor & Francis
Bundle methods are at the moment the most efficient and promising methods for nonsmooth
optimization. They have been successfully used in many practical applications, for example …
optimization. They have been successfully used in many practical applications, for example …
A novel Lagrangian relaxation approach for a hybrid flowshop scheduling problem in the steelmaking-continuous casting process
One of the largest bottlenecks in iron and steel production is the steelmaking-continuous
casting (SCC) process, which consists of steel-making, refining and continuous casting. The …
casting (SCC) process, which consists of steel-making, refining and continuous casting. The …
Level bundle methods for oracles with on-demand accuracy
W de Oliveira, C Sagastizábal - Optimization Methods and …, 2014 - Taylor & Francis
For non-smooth convex optimization, we consider level bundle methods built using an
oracle that computes values for the objective function and a subgradient at any given …
oracle that computes values for the objective function and a subgradient at any given …
[图书][B] Inverse imaging with Poisson data: from cells to galaxies
M Bertero, P Boccacci, V Ruggiero - 2018 - iopscience.iop.org
Inverse Imaging with Poisson Data is an invaluable resource for graduate students,
postdocs and researchers interested in the application of inverse problems to the domains of …
postdocs and researchers interested in the application of inverse problems to the domains of …
Recent advances in variable metric first-order methods
Minimization problems often occur in modeling phenomena dealing with real-life
applications that nowadays handle large-scale data and require real-time solutions. For …
applications that nowadays handle large-scale data and require real-time solutions. For …
Bundle methods in the XXIst century: A bird's-eye view
W Oliveira, C Sagastizábal - Pesquisa Operacional, 2014 - SciELO Brasil
Bundle methods are often the algorithms of choice for nonsmooth convex optimization,
especially if accuracy in the solution and reliability are a concern. We review several …
especially if accuracy in the solution and reliability are a concern. We review several …
[图书][B] Convergence of a simple subgradient level method
JL Goffin, KC Kiwiel - 1998 - academia.edu
Convergence of a simple subgradient level method Page 1 Math. Program. 85: 207–211 (1999)
/ DOI 10.1007/s10107980003a © Springer-Verlag 1999 Jean-Louis Goffin · Krzysztof C. Kiwiel …
/ DOI 10.1007/s10107980003a © Springer-Verlag 1999 Jean-Louis Goffin · Krzysztof C. Kiwiel …
A doubly stabilized bundle method for nonsmooth convex optimization
W de Oliveira, M Solodov - Mathematical programming, 2016 - Springer
We propose a bundle method for minimizing nonsmooth convex functions that combines
both the level and the proximal stabilizations. Most bundle algorithms use a cutting-plane …
both the level and the proximal stabilizations. Most bundle algorithms use a cutting-plane …
[图书][B] Large-scale nonsmooth optimization: variable metric bundle method with limited memory
M Haarala - 2004 - jyx.jyu.fi
Many practical optimization problems involve nonsmooth (that is, not necessarily
differentiable) functions of hundreds or thousands of variables. In such problems, the direct …
differentiable) functions of hundreds or thousands of variables. In such problems, the direct …