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Fully Dynamic Algorithms for Knapsack Problems with Polylogarithmic Update Time

Authors Franziska Eberle , Nicole Megow , Lukas Nölke , Bertrand Simon , Andreas Wiese

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Author Details

Franziska Eberle
  • Faculty of Mathematics and Computer Science, University of Bremen, Germany
Nicole Megow
  • Faculty of Mathematics and Computer Science, University of Bremen, Germany
Lukas Nölke
  • Faculty of Mathematics and Computer Science, University of Bremen, Germany
Bertrand Simon
  • IN2P3 Computing Center, CNRS, Villeurbanne, France
Andreas Wiese
  • Department of Industrial Engineering, University of Chile, Santiago, Chile

Funding

This work is partly funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) - Project Number 146371743 - TRR 89 Invasive Computing.

Acknowledgements

We thank Martin Böhm, Peter Kling, and Jens Schlöter for the fruitful discussions.

Cite As Get BibTex

Franziska Eberle, Nicole Megow, Lukas Nölke, Bertrand Simon, and Andreas Wiese. Fully Dynamic Algorithms for Knapsack Problems with Polylogarithmic Update Time. In 41st IARCS Annual Conference on Foundations of Software Technology and Theoretical Computer Science (FSTTCS 2021). Leibniz International Proceedings in Informatics (LIPIcs), Volume 213, pp. 18:1-18:17, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2021) https://doi.org/10.4230/LIPIcs.FSTTCS.2021.18

Abstract

Knapsack problems are among the most fundamental problems in optimization. In the Multiple Knapsack problem, we are given multiple knapsacks with different capacities and items with values and sizes. The task is to find a subset of items of maximum total value that can be packed into the knapsacks without exceeding the capacities. We investigate this problem and special cases thereof in the context of dynamic algorithms and design data structures that efficiently maintain near-optimal knapsack solutions for dynamically changing input. More precisely, we handle the arrival and departure of individual items or knapsacks during the execution of the algorithm with worst-case update time polylogarithmic in the number of items. As the optimal and any approximate solution may change drastically, we maintain implicit solutions and support polylogarithmic time query operations that can return the computed solution value and the packing of any given item.
While dynamic algorithms are well-studied in the context of graph problems, there is hardly any work on packing problems (and generally much less on non-graph problems). Motivated by the theoretical interest in knapsack problems and their practical relevance, our work bridges this gap.

Subject Classification

ACM Subject Classification
  • Theory of computation → Packing and covering problems
Keywords
  • Fully dynamic algorithms
  • knapsack problem
  • approximation schemes

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