Daniel Kuhn

Cette personne a quitté l’EPFL

À propos
Confidentialité
Mentions légales

Graph Chatbot

Publications associées (69)

Page 4 sur 4

The Decision Rule Approach to Optimisation under Uncertainty: Methodology and Applications

Daniel Kuhn, Wolfram Wiesemann

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naively partition or discretize the support of the random problem parameters are limited to sma ...

2019

K-Adaptability in Two-Stage Distributionally Robust Binary Programming

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto

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

Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization

Daniel Kuhn, Wolfram Wiesemann, Napat Rujeerapaiboon, Kilian Schindler

Plain vanilla K-means clustering is prone to produce unbalanced clusters and suffers from outlier sensitivity. To mitigate both shortcomings, we formulate a joint outlier-detection and clustering problem, which assigns a prescribed number of datapoints to ...

SIAM Publications2019

A Distributionally Robust Perspective on Uncertainty Quantification and Chance Constrained Programming

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto

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

Decision Rule Bounds for Two-Stage Stochastic Bilevel Programs

Daniel Kuhn

We study stochastic bilevel programs where the leader chooses a binary here-and-now decision and the follower responds with a continuous wait-and-see-decision. Using modern decision rule approximations, we construct lower bounds on an optimistic version an ...

SIAM Publications2018

Data-Driven Chance Constrained Programs over Wasserstein Balls

Daniel Kuhn, Wolfram Wiesemann

We provide an exact deterministic reformulation for data-driven chance constrained programs over Wasserstein balls. For individual chance constraints as well as joint chance constraints with right-hand side uncertainty, our reformulation amounts to a mixed ...

2024

A Planner-Trader Decomposition for Multi-Market Hydro Scheduling

Daniel Kuhn, Wolfram Wiesemann, Napat Rujeerapaiboon, Kilian Schindler

Peak/off-peak spreads on European electricity forward and spot markets are eroding due to the ongoing nuclear phaseout and the steady growth in photovoltaic capacity. The reduced profitability of peak/off- peak arbitrage forces hydropower producers to reco ...

2024

Ambiguous Joint Chance Constraints under Mean and Dispersion Information

Daniel Kuhn, Wolfram Wiesemann, Grani Adiwena Hanasusanto

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

Financial Optimization: Optimization Paradigms and Financial Planning under Uncertainty

Daniel Kuhn

Springer2015