- Online Bin Packing with Advice.
- Joan Boyar, Shahin Kamali, Kim S. Larsen, and Alejandro López-Ortiz.
Algorithmica, 74(1): 507-527, 2016.
We consider the online bin packing problem under the advice complexity
model where the "online constraint" is relaxed and an algorithm receives
partial information about the future items. We provide tight upper and
lower bounds for the amount of advice an algorithm needs to achieve an
We also introduce an algorithm that, when provided with
log n + o(log n)
bits of advice, achieves a competitive ratio of
for the general problem. This algorithm is simple and is expected to
find real-world applications. We introduce another algorithm that
receives 2n + o(n)
bits of advice and achieves a competitive ratio
of 4/3 + ε
. Finally, we provide a lower bound argument that
implies that advice of linear size is required for an algorithm to achieve
a competitive ratio better than 9/8
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