Packing a Knapsack of Unknown Capacity
release_llvtim22lvhg3kofaap7oyag34
by
Yann Disser and Max Klimm and Nicole Megow and Sebastian Stiller
2013
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 alpha>1, the problem of deciding whether a given universal policy
achieves a factor of alpha is coNP-complete. If alpha 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 alpha, whether a set
of items admits a universal policy with factor alpha, even if all items have
unit densities.
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