Improved Results for Knapsack with Removal

Gehnen, Matthias; Güven, Kübra; Hächler, Valentin; Komm, Dennis; Královič, Richard

doi:10.4230/LIPIcs.MFCS.2026.51

Abstract

We study the proportional online knapsack problem with removal. For randomized algorithms, we tighten the gap between the current lower and upper bounds on the expected competitive ratio by presenting a lower bound of roughly 1.27. We further study this problem under the model of online algorithms with predictions. Our lower bound arguments are agnostic to the type of available prediction, which makes them very general. For deterministic algorithms, we provide a tightly matching upper bound on the competitive ratio for a specific kind of weight prediction.

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Matthias Gehnen, Kübra Güven, Valentin Hächler, Dennis Komm, and Richard Královič. Improved Results for Knapsack with Removal. In 51st International Symposium on Mathematical Foundations of Computer Science (MFCS 2026). Leibniz International Proceedings in Informatics (LIPIcs), Volume 386, pp. 51:1-51:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2026) https://doi.org/10.4230/LIPIcs.MFCS.2026.51

Author Details

Matthias Gehnen

Department of Computer Science, RWTH Aachen University, Germany

Kübra Güven

Department of Computer Science, RWTH Aachen University, Germany

Valentin Hächler

Department of Computer Science, ETH Zurich, Switzerland

Dennis Komm

Department of Computer Science, ETH Zurich, Switzerland

Richard Královič

Department of Computer Science, ETH Zurich, Switzerland

References

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Improved Results for Knapsack with Removal

Authors Matthias Gehnen , Kübra Güven, Valentin Hächler, Dennis Komm , Richard Královič

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