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We solve Skorokhod's embedding problem for Brownian mostion with linear drift $(W_t + \kappa t)_{t\ge 0}$ by means of techniques of stochastic control theory. The search for a stopping time $T$ such that the law of $W_T + \kappa T$ coincides with a prescribed law $\mu$ processing the first moment is based on solutions of backward stochastic differential equations of quadratic type. Theis new approach generalizes an approach by Bass [BAS] of the classical version of Skorokhod's embedding problem using martingale representation techniques.
We solve Skorokhod's embedding problem for Brownian motion with linear drift $(W_t+ \kappa t)_{t\geq 0}$ by means of techniques of stochastic control theory. The search for a stopping time
$T$ such that the law of $W_T + \kappa T$ coincides with a prescribed law $\mu$ possessing the first
moment is based on solutions of backward stochastic differential equations of quadratic
type. This new approach generalizes an approach by Bass [Bas] of the classical version of
Skorokhod's embedding problem using martingale representation techniques.
A Branch-Cut-And-Price Algorithm for a Combined Buy-at-Bulk Network Design Facility Location Problem
(2014)
In the combined buy-at-bulk network design facility location
problem we are given an undirected network with a set of potential facilities and a set of clients with demands. In addition, we are also provided a set of cable types with each cable type having a capacity and cost per unit length. The cost to capacity ratio decreases from large to small
cables following economies of scale. A network planner is expected to determine a set of facilities to open and install cables along the edges of the network in order to route the demands of the clients to some open facility. The capacities of the installed cable must be able to support the demands of the clients routed along that edge.The objective is to minimize the cost that is paid for opening facilities and installing cables. We model the problem as an integer program and propose a branch-cut-and-price algorithm for solving it. We study the effect of two family of valid inequalities that naturally emerge from the model. We present the results of our implementation that were tested on a set of large real world instances.
We develop a behavioural approach to linear, time-varying, differential algebraic systems.
The analysis is \almost everywhere" in the sense that the statements hold on R T, where
T is a discrete set. Controllability, observability and autonomy is introduced and related to
the behaviour of the system. Classical results on the behaviour of time-invariant systems are
studied in the context of time-varying systems.
Diffusion processes are relevant for a variety of phenomena in the natural sciences, including
diffusion of cells or biomolecules within cells, diffusion of molecules on a membrane or surface,
diffusion of a molecular conformation within a complex energy landscape. Many experimental
tools exist now to track such diffusive motions in single cells or molecules, including high-resolution
light microscopy, optical tweezers, fluorescence quenching, and Förster resonance energy transfer
(FRET). Experimental observations are most often indirect and incomplete: (1) They do not
directly reveal the potential or diffusion constants that govern the diffusion process, (2) they have
limited time and space resolution, and (3) the highest-resolution experiments do not track the
motion directly but rather probe it stochastically by recording single events, such as photons,
whose properties depend on the state of the system under investigation.
Here, we propose a general Bayesian framework to model diffusion processes with nonlinear
drift based on incomplete observations as generated by various types of experiments. A maximum
penalized likelihood estimator is given as well as a Gibbs sampling method that allows to estimate
the trajectories that have caused the measurement, the nonlinear drift or potential function and
the noise or diffusion matrices, as well as uncertainty estimates of these properties. The approach
is illustrated on numerical simulations of FRET experiments where it is shown that trajectories,
potentials and diffusion constants can be efficiently and reliably estimated even in cases with little
statistics or non-equilibrium measurement conditions.
We consider a one–dimensional coupled stationary Schrödinger drift–diffusion model for quantum
semiconductor device simulations. The device domain is decomposed into a part with large quantum
effects (quantum zone) and a part where quantum effects are negligible (classical zone). We give
boundary conditions at the classic–quantum interface which are current preserving. Collisions within
the quantum zone are introduced via a Pauli master equation. To illustrate the validity we apply the
model to three resonant tunneling diodes
We present a globally convergent method for the solution of frictionless large deformation contact problems involving hyperelastic materials.
For the discretisation we apply the dual mortar method which is known to be more stable than node-to-segment approaches. The resulting non-convex constrained minimisation problems are solved using a filter–trust-region scheme.
This method combines several techniques from non-linear optimisation to achieve global convergence towards first-order optimal points. To speed up the method inexact linearisations of the non-penetration constraint are used
whenever the current iterate is far away from a critical point. A monotone multigrid method is applied for the fast solution of the constrained Newton
problems.
We introduce a behavioural approach to linear, time-varying, differential algebraic
(descriptor) systems. The analysis is \almost global" in the sense that the analysis is
not restricted to an interval I R but is allowed for the \time axis" RnT, where T is
a discrete set of critical points, at which the solution may exhibit a finite escape time.
Controllable, observable, autonomous, and adjoint behaviour for linear time-varying
descriptor systems is introduced and characterized.
Systems of rail-mounted vehicles play a key role in many logistics applications, and the efficiency of their operation frequently has a significant impact on the overall performance of the surrounding production environment. In theory, assigning transport requests to the vehicles of such systems and scheduling their execution amounts to finding k tours on a common line, where tours may never cross each other in time--dynamic collision constraints need to be respected. The goal is to minimize the makespan for a given set of transport requests.
We establish a model capturing the core challenges in transport planning problems of this type and relate it to other models in literature. After proving NP-hardness for a basic version of the problem, the large part of the paper is dedicated to devising various fast heuristic algorithms suitable for practice. We present computational results regarding the performance of the algorithms proposed for several classes of problem instances.
Let $\Upsilon$ be a three-dimensional Lipschitz polyhedron, and assume that the matrix function $\mu$ is piecewise constant on a polyhedral partition of $\Upsilon$. Based on regularity results for solutions to two-dimensional anisotropic transmission problems near corner points we obtain conditions on $\mu$ and the intersection angles between interfaces and $\partial \Upsilon$ ensuring that the operator $-\nabla \cdot \mu \nabla$ maps the Sobolev space $W^1,q_0(\Upsilon)$ isomorphically onto $W^-1,q(\Upsilon)$ for some $q > 3$.
$\mu$-values and spectral value sets for linear perturbation classes defined by a scalar product
(2007)
We study the variation of the spectrum of matrices
under perturbations which are self- or skew-adjoint
with respect to a scalar product.
Computable formulae are given for the associated
$\mu$-values. The results can be used to calculate spectral value
sets for the perturbation classes under consideration.
We discuss the special case of
complex Hamiltonian perturbations of a Hamiltonian matrix in detail.