https://www.alexandria.unisg.ch
University of St.Gallenennew publications - Daniel KuhnAlexandria::new publicationsRapid Design Space visualisation through hardware/software partitioningSpacey, S. A., Luk, W., Kelly, P. H., & Kuhn, D. (2009). Rapid Design Space visualisation through hardware/software partitioning. In 2009 5th Southern Conference on Programmable Logic (SPL), pp.159-164: Institute of Electrical and Electronics Engineers (IEEE). - ISBN 978-1-4244-3847-1. --- This paper introduces the 3SP Design Space Exploration System. 3SP automatically quantifies acceleration opportunities for programs across a wide range of heterogeneous architectures to allow designers to identify promising implementation platforms before investing in a particular hardware/ software codesign. 3SP uses a novel program execution model to integrate comprehensive hardware ...
https://www.alexandria.unisg.ch/publications/60723
2010-03-08Maximizing the net present value of a project under uncertaintyWiesemann, W., Kuhn, D., & Rustem, B. (2010). Maximizing the net present value of a project under uncertainty. European Journal of Operational Research, 202(2), 356-367, DOI:10.1016/j.ejor.2009.05.045. --- We address the maximization of a projectâ€™s expected net present value when the activity durations and cash flows are described by a discrete set of alternative scenarios with associated occurrence probabilities. In this setting, the choice of scenario-independent activity start times frequently leads to infeasible schedules or severe losses in revenues. We suggest to determine an optimal target...
https://www.alexandria.unisg.ch/publications/60722
2010-03-08Analysis of the rebalancing frequency in log-optimal portfolio selectionKuhn, D., & Luenberger, D. G. (2010). Analysis of the rebalancing frequency in log-optimal portfolio selection. Quantitative Finance, 10(2), 221-234, DOI:10.1080/14697680802629400. --- In a dynamic investment situation, the right timing of portfolio revisions and adjustments is essential to sustain long-term growth. A high rebalancing frequency reduces the portfolio performance in the presence of transaction costs, whereas a low rebalancing frequency entails a static investment strategy that hardly reacts to changing market conditions. This article studies a family of portfolio...
https://www.alexandria.unisg.ch/publications/60683
2010-03-05An Information-Based Approximation Scheme for Stochastic Optimization Problems in Continuous TimeKuhn, D. (2009). An Information-Based Approximation Scheme for Stochastic Optimization Problems in Continuous Time. Mathematics of Operations Research, 34(2), 428-444. --- Dynamic stochastic optimization problems with a large (possibly infinite) number of decision stages and high-dimensional state vectors are inherently difficult to solve. In fact, scenario tree-based algorithms are unsuitable for problems with many stages, while dynamic programming-type techniques are unsuitable for problems with many state variables. This paper proposes a stage aggregation scheme...
https://www.alexandria.unisg.ch/publications/60651
2010-03-04Convergent Bounds for Stochastic Programs with Expected Value ConstraintsKuhn, D. (2009). Convergent Bounds for Stochastic Programs with Expected Value Constraints. Journal of Optimization Theory and Applications, 141(3), 597-618. --- This article describes a bounding approximation scheme for convex multistage stochastic programs (MSP) that constrain the conditional expectation of some decision-dependent random variables. Expected value constraints of this type are useful for modelling a decision makerâ€™s risk preferences, but they may also arise as artifacts of stage-aggregation. We develop two finite-dimensional approximate...
https://www.alexandria.unisg.ch/publications/60650
2010-03-04Dynamic Mean-Variance Portfolio Analysis under Model RiskKuhn, D., Parpas, P., Rustem, B., & Fonseca, R. (2009). Dynamic Mean-Variance Portfolio Analysis under Model Risk. Journal of Computational Finance(12 (4)), 91-115. --- The classical Markowitz approach to portfolio selection is compromised by two major shortcomings. First, there is considerable model risk with respect to the distribution of asset returns. Particularly, mean returns are notoriously difficult to estimate. Moreover, the Markowitz approach is static in that it does not account for the possibility of portfolio rebalancing within the investment ...
https://www.alexandria.unisg.ch/publications/60648
2010-03-04A Stochastic Programming Approach for QoS-Aware Service CompositionWiesemann, W., Hochreiter, R., & Kuhn, D. (2008). A Stochastic Programming Approach for QoS-Aware Service Composition. In , pp.226-233. Los Alamitos: IEEE Computer Society. - ISBN 978-0-7695-3156-4. --- We formulate the service composition problem as a multi-objective stochastic program which simultaneously optimizes the following quality of service (QoS) parameters: workflow duration, service invocation costs, availability, and reliability. All of these quality measures are modelled as decision-dependent random variables. Our model minimizes the average value-at-risk (AVaR) of the workflow ...
https://www.alexandria.unisg.ch/publications/60643
2010-03-04Stochastic optimization of investment planning problems in the electric power industryKuhn, D., Parpas, P., & Rustem, B. (2008). Stochastic optimization of investment planning problems in the electric power industry. In Energy Systems Engineering (pp. 215-230). Weinheim: Wiley-VCH. - ISBN 978-3-527-31694-6. ---
https://www.alexandria.unisg.ch/publications/60639
2010-03-04Threshold Accepting Approach to Improve Bound-based Approximations for Portfolio OptimizationKuhn, D., Parpas, P., & Rustem, B. (2008). Threshold Accepting Approach to Improve Bound-based Approximations for Portfolio Optimization. In Computational Methods in Financial Engineering (pp. 3-26). Berlin, Heidelberg: Springer. - ISBN 978-3-540-77957-5. --- A discretization scheme for a portfolio selection problem is discussed. The model is a benchmark relative, mean-variance optimization problem in continuous time. In order to make the model computationally tractable, it is discretized in time and space. This approximation scheme is designed in such a way that the optimal values of the approximate problems yield bounds on the optimal value of the ...
https://www.alexandria.unisg.ch/publications/60638
2010-03-04Aggregation and discretization in multistage stochastic programmingKuhn, D. (2008). Aggregation and discretization in multistage stochastic programming. Mathematical Programming, Series A, 113(1), 61-94, DOI:10.1007/s10107-006-0048-6. --- Multistage stochastic programs have applications in many areas and support policy makers in finding rational decisions that hedge against unforeseen negative events. In order to ensure computational tractability, continuous-state stochastic programs are usually discretized; and frequently, the curse of dimensionality dictates that decision stages must be aggregated. In this article we construct ...
https://www.alexandria.unisg.ch/publications/60637
2010-03-04