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Wolfram Wiesemann

Related publications (32)

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A Distributionally Robust Perspective on Uncertainty Quantification and Chance Constrained Programming

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

The objective of uncertainty quantification is to certify that a given physical, engineering or economic system satisfies multiple safety conditions with high probability. A more ambitious goal is to actively influence the system so as to guarantee and mai ...

Springer Verlag2015

The Stochastic Time-Constrained Net Present Value Problem

Daniel Kuhn, Wolfram Wiesemann

The successful management of capital-intensive development and engineering projects requires a careful timing of the involved cash in- and outflows. To this end, the project management literature proposes to schedule the project activities so as to maximiz ...

Springer International Publishing2015

Distributionally Robust Convex Optimization

Daniel Kuhn, Wolfram Wiesemann

Distributionally robust optimization is a paradigm for decision-making under uncertainty where the uncertain problem data is governed by a probability distribution that is itself subject to uncertainty. The distribution is then assumed to belong to an ambi ...

2014

Robust Markov Decision Processes

Daniel Kuhn, Wolfram Wiesemann

Markov decision processes (MDPs) are powerful tools for decision making in uncertain dynamic environments. However, the solutions of MDPs are of limited practical use because of their sensitivity to distributional model parameters, which are typically unkn ...

2013

Robust Software Partitioning with Multiple Instantiation

Daniel Kuhn, Wolfram Wiesemann

The purpose of software partitioning is to assign code segments of a given computer program to a range of execution locations such as general-purpose processors or specialist hardware components. These execution locations differ in speed, communication cha ...

2012

Multi-resource allocation in stochastic project scheduling

Daniel Kuhn, Wolfram Wiesemann

We propose a resource allocation model for project scheduling. Our model accommodates multiple resources and decision-dependent activity durations inspired by microeconomic theory. First, we elaborate a deterministic problem formulation. In a second stage, ...

2012

Robust resource allocations in temporal networks

Daniel Kuhn, Wolfram Wiesemann

Temporal networks describe workflows of time-consuming tasks whose processing order is constrained by precedence relations. In many cases, the durations of the network tasks can be influenced by the assignment of resources. This leads to the problem of sel ...

2012

Primal and dual linear decision rules in stochastic and robust optimization

Daniel Kuhn, Wolfram Wiesemann

Linear stochastic programming provides a flexible toolbox for analyzing real-life decision situations, but it can become computationally cumbersome when recourse decisions are involved. The latter are usually modeled as decision rules, i.e., functions of t ...

2011

SQPR: Stream query planning with reuse

Daniel Kuhn, Wolfram Wiesemann

When users submit new queries to a distributed stream processing system (DSPS), a query planner must allocate physical resources, such as CPU cores, memory and network bandwidth, from a set of hosts to queries. Allocation decisions must provide the correct ...

IEEE2011

Hedging Electricity Swing Options in Incomplete Markets

Daniel Kuhn, Wolfram Wiesemann

The deregulation of electricity markets renders public utilities vulnerable to the high volatility of electricity spot prices. This price risk is effectively mitigated by swing options, which allow the option holder to buy electric energy from the option w ...

2011