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Packing a Knapsack of Unknown Capacity

Authors Yann Disser, Max Klimm, Nicole Megow, Sebastian Stiller



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LIPIcs.STACS.2014.276.pdf
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Yann Disser
Max Klimm
Nicole Megow
Sebastian Stiller

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Yann Disser, Max Klimm, Nicole Megow, and Sebastian Stiller. Packing a Knapsack of Unknown Capacity. In 31st International Symposium on Theoretical Aspects of Computer Science (STACS 2014). Leibniz International Proceedings in Informatics (LIPIcs), Volume 25, pp. 276-287, Schloss Dagstuhl - Leibniz-Zentrum für Informatik (2014)
https://doi.org/10.4230/LIPIcs.STACS.2014.276

Abstract

We study the problem of packing a knapsack without knowing its capacity. Whenever we attempt to pack an item that does not fit, the item is discarded; if the item fits, we have to include it in the packing. We show that there is always a policy that packs a value within factor 2 of the optimum packing, irrespective of the actual capacity. If all items have unit density, we achieve a factor equal to the golden ratio. Both factors are shown to be best possible. In fact, we obtain the above factors using packing policies that are universal in the sense that they fix a particular order of the items and try to pack the items in this order, independent of the observations made while packing. We give efficient algorithms computing these policies. On the other hand, we show that, for any a>1, the problem of deciding whether a given universal policy achieves a factor of a is coNP-complete. If a is part of the input, the same problem is shown to be coNP-complete for items with unit densities. Finally, we show that it is coNP-hard to decide, for given a, whether a set of items admits a universal policy with factor a, even if all items have unit densities.
Keywords
  • Knapsack
  • unknown capacity
  • robustness
  • approximation algorithms

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