Optimization problems under uncertain conditions abound in many real-life applications. While solution approaches for probabilistic constraints are often developed in case the uncertainties can be assumed to follow a certain probability distribution, robust approaches are usually applied in case solutions are sought that are feasible for all realizations of uncertainties within some predefined uncertainty set. As many applications contain different types of uncertainties that require robust as well as probabilistic treatments, we deal with a class of joint probabilistic/robust constraints. Focusing on complex uncertain gas network optimization problems, we show the relevance of this class of problems for the task of maximizing free booked c...
Diese Arbeit liefert, in den ersten beiden Kapiteln einen allgemeinen Überblick über die klassischen...
In this paper we study ambiguous chance constrained problems where the distributions of the random p...
This paper proposes a new optimization techniques for the optimization a gas processing plant uncert...
Optimization problems under uncertain conditions abound in many real-life applications. While soluti...
Optimization problems under uncertain conditions abound in many real-life applications. While soluti...
Optimization problems under uncertain conditions abound in many real-life applications. While soluti...
We present a novel mathematical algorithm to assist gas network operators in managing uncertainty, w...
We present a novel mathematical algorithm to assist gas network operators in managing uncertainty, w...
The question for the capacity of a given gas network appears as an essential question that network o...
We present an adaptive grid refinement algorithm to solve probabilistic optimization problems with i...
We develop a general methodology for deriving probabilistic guarantees for solutions of robust optim...
Today, natural gas is one of the most important sources of energy and is regarded as a key instrumen...
In optimization problems involving uncertainty, probabilistic constraints are an important tool for ...
the thesis deals with important problem of planning of telecommunication networks (and other network...
Diese Arbeit liefert, in den ersten beiden Kapiteln einen allgemeinen Überblick über die klassischen...
In this paper we study ambiguous chance constrained problems where the distributions of the random p...
This paper proposes a new optimization techniques for the optimization a gas processing plant uncert...
Optimization problems under uncertain conditions abound in many real-life applications. While soluti...
Optimization problems under uncertain conditions abound in many real-life applications. While soluti...
Optimization problems under uncertain conditions abound in many real-life applications. While soluti...
We present a novel mathematical algorithm to assist gas network operators in managing uncertainty, w...
We present a novel mathematical algorithm to assist gas network operators in managing uncertainty, w...
The question for the capacity of a given gas network appears as an essential question that network o...
We present an adaptive grid refinement algorithm to solve probabilistic optimization problems with i...
We develop a general methodology for deriving probabilistic guarantees for solutions of robust optim...
Today, natural gas is one of the most important sources of energy and is regarded as a key instrumen...
In optimization problems involving uncertainty, probabilistic constraints are an important tool for ...
the thesis deals with important problem of planning of telecommunication networks (and other network...
Diese Arbeit liefert, in den ersten beiden Kapiteln einen allgemeinen Überblick über die klassischen...
In this paper we study ambiguous chance constrained problems where the distributions of the random p...
This paper proposes a new optimization techniques for the optimization a gas processing plant uncert...