Publications de Daniel Kuhn | EPFL Graph Search

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Ambiguous Joint Chance Constraints under Mean and Dispersion Information

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

We study joint chance constraints where the distribution of the uncertain parameters is only known to belong to an ambiguity set characterized by the mean and support of the uncertainties and by an upper bound on their dispersion. This setting gives rise t ...

Informs2017

Optimal Financial Decision Making Under Uncertainty

Daniel Kuhn

We use a fairly general framework to analyze a rich variety of financial optimization models presented in the literature, with emphasis on contributions included in this volume and a related special issue of OR Spectrum. We do not aim at providing readers ...

Springer International Publishing2017

Robust Growth-Optimal Portfolios

Daniel Kuhn, Napat Rujeerapaiboon, Wolfram Wiesemann

The growth-optimal portfolio is designed to have maximum expected log-return over the next rebalancing period. Thus, it can be computed with relative ease by solving a static optimization problem. The growth-optimal portfolio has sparked fascination among ...

Informs2016

A Comment on “Computational Complexity of Stochastic Programming Problems”

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

Although stochastic programming problems were always believed to be computationally challenging, this perception has only recently received a theoretical justification by the seminal work of Dyer and Stougie (Mathematical Programming A, 106(3):423–432, 200 ...

Springer Heidelberg2016

Distributionally Robust Control of Constrained Stochastic Systems

Daniel Kuhn

We investigate the control of constrained stochastic linear systems when faced with only limited information regarding the disturbance process, i.e. when only the first two moments of the disturbance distribution are known. We consider two types of distrib ...

Institute of Electrical and Electronics Engineers2016

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

We propose to approximate two-stage distributionally robust programs with binary recourse decisions by their associated K-adaptability problems, which pre-select K candidate second-stage policies here-and-now and implement the best of these policies once t ...

Elsevier Science Bv2016

Interdiction Games on Markovian PERT Networks

Daniel Kuhn, Wolfram Wiesemann, Eli Gutin

In a stochastic interdiction game a proliferator aims to minimize the expected duration of a nuclear weapons development project, and an interdictor endeavors to maximize the project duration by delaying some of the project tasks. We formulate static and d ...

Informs2015

Generalized Decision Rule Approximations for Stochastic Programming via Liftings

Daniel Kuhn, Wolfram Wiesemann

Stochastic programming provides a versatile framework for decision-making under uncertainty, but the resulting optimization problems can be computationally demanding. It has recently been shown that, primal and dual linear decision rule approximations can ...

Springer Verlag2015

K-Adaptability in Two-Stage Robust Binary Programming

Daniel Kuhn, Grani Adiwena Hanasusanto, Wolfram Wiesemann

Over the last two decades, robust optimization has emerged as a computationally attractive approach to formulate and solve single-stage decision problems affected by uncertainty. More recently, robust optimization has been successfully applied to multi-sta ...

Informs2015

Daniel Kuhn

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Ambiguous Joint Chance Constraints under Mean and Dispersion Information

Optimal Financial Decision Making Under Uncertainty

Robust Growth-Optimal Portfolios

A Comment on “Computational Complexity of Stochastic Programming Problems”

Distributionally Robust Control of Constrained Stochastic Systems

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Generalized Gauss Inequalities via Semidefinite Programming

Interdiction Games on Markovian PERT Networks

Generalized Decision Rule Approximations for Stochastic Programming via Liftings

K-Adaptability in Two-Stage Robust Binary Programming

A Comment on “Computational Complexity of Stochastic Programming Problems”

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Generalized Gauss Inequalities via Semidefinite Programming

K-Adaptability in Two-Stage Robust Binary Programming

Distributionally Robust Control of Constrained Stochastic Systems

Ambiguous Joint Chance Constraints under Mean and Dispersion Information

Optimal Financial Decision Making Under Uncertainty

Generalized Decision Rule Approximations for Stochastic Programming via Liftings

Robust Growth-Optimal Portfolios

Interdiction Games on Markovian PERT Networks