2 citations · 5 across the 5 of their papers we have counts for
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Robust Conic Satisficing
Arjun Ramachandra, Napat Rujeerapaiboon, Melvyn Sim
In practical optimization problems, we typically model uncertainty as a random variable though its true probability distribution is unobservable to the decision maker. Historical d…
A Planner-Trader Decomposition for Multi-Market Hydro Scheduling
Kilian Schindler, Napat Rujeerapaiboon, Daniel Kuhn +1
Peak/off-peak spreads on European electricity forward and spot markets are eroding due to the ongoing nuclear phaseout in Germany and the steady growth in photovoltaic capacity. Th…
Size Matters: Cardinality-Constrained Clustering and Outlier Detection via Conic Optimization
Napat Rujeerapaiboon, Kilian Schindler, Daniel Kuhn +1
Plain vanilla K-means clustering has proven to be successful in practice, yet it suffers from outlier sensitivity and may produce highly unbalanced clusters. To mitigate both short…
Scenario Reduction Revisited: Fundamental Limits and Guarantees
Napat Rujeerapaiboon, Kilian Schindler, Daniel Kuhn +1
The goal of scenario reduction is to approximate a given discrete distribution with another discrete distribution that has fewer atoms. We distinguish continuous scenario reduction…