Packing a Knapsack of Unknown Capacity
Yann Disser, Max Klimm, Nicole Megow, Sebastian Stiller · SIAM Journal on Discrete Mathematics · 2017
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 $\varphi\approx1.618$. 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 in the beginning and try to pack the items in this order, without changing the order later on. 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 ${\mathsf{coNP}}$-complete. If $\alpha$ is part of the input, the same problem is shown to be ${\mathsf{coNP}}$-complete for items with unit densities. Finally, we show that it is ${\mathsf{coNP}}$-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.