[图书][B] Einführung in operations research
W Domschke, A Drexl, R Klein, A Scholl - 2015 - books.google.com
Didaktisch effektives und effizientes Standardwerk in der 9. Auflage: Dieses Buch entstand
aus Vorlesungen zur Einführung in Operations Research (OR) für Studierende der Betriebs …
aus Vorlesungen zur Einführung in Operations Research (OR) für Studierende der Betriebs …
Photons in-numbers out: perspectives in quantitative fluorescence microscopy for in situ protein counting
KS Gruβmayer, K Yserentant… - Methods and applications …, 2019 - iopscience.iop.org
The full understanding of cellular functions requires information about protein numbers for
various biomolecular assemblies and their dynamics, which can be partly accessed by …
various biomolecular assemblies and their dynamics, which can be partly accessed by …
A novel p-harmonic descent approach applied to fluid dynamic shape optimization
PM Müller, N Kühl, M Siebenborn, K Deckelnick… - Structural and …, 2021 - Springer
We introduce a novel method for the implementation of shape optimization for non-
parameterized shapes in fluid dynamics applications, where we propose to use the shape …
parameterized shapes in fluid dynamics applications, where we propose to use the shape …
Optimal insurance contract design with government disaster relief
S Hinck - Journal of Risk and Insurance, 2024 - Wiley Online Library
I examine the design of optimal insurance contracts considering the possibility of
government disaster relief payments. This work focuses on the impact of (risky and …
government disaster relief payments. This work focuses on the impact of (risky and …
Nonlinear FETI-DP and BDDC methods: a unified framework and parallel results
Parallel Newton--Krylov FETI-DP (Finite Element Tearing and Interconnecting---Dual-Primal)
domain decomposition methods are fast and robust solvers, eg, for nonlinear implicit …
domain decomposition methods are fast and robust solvers, eg, for nonlinear implicit …
A bilevel approach for parameter learning in inverse problems
G Holler, K Kunisch, RC Barnard - Inverse Problems, 2018 - iopscience.iop.org
A learning approach for selecting regularization parameters in multi-penalty Tikhonov
regularization is investigated. It leads to a bilevel optimization problem, where the lower …
regularization is investigated. It leads to a bilevel optimization problem, where the lower …
On the solution of convex bilevel optimization problems
S Dempe, S Franke - Computational Optimization and Applications, 2016 - Springer
An algorithm is presented for solving bilevel optimization problems with fully convex lower
level problems. Convergence to a local optimal solution is shown under certain weak …
level problems. Convergence to a local optimal solution is shown under certain weak …
Multi-objective yield optimization for electrical machines using Gaussian processes to learn faulty design
MC Huber, M Fuhrländer… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
This work deals with the design optimization of electrical machines under the consideration
of manufacturing uncertainties. In order to efficiently quantify the uncertainty, a hybrid Gauss …
of manufacturing uncertainties. In order to efficiently quantify the uncertainty, a hybrid Gauss …
A novel density based approach for topology optimization of stokes flow
A new method for performing density-based topology optimization for Stokes flow is
presented. It differs from previous approaches in the way the underlying mixed integer …
presented. It differs from previous approaches in the way the underlying mixed integer …
Hermite least squares optimization: a modification of BOBYQA for optimization with limited derivative information
M Fuhrländer, S Schöps - Optimization and Engineering, 2023 - Springer
Derivative-free optimization tackles problems, where the derivatives of the objective function
are unknown. However, in practical optimization problems, the derivatives of the objective …
are unknown. However, in practical optimization problems, the derivatives of the objective …