György, András and Lugosi, Gábor and Ottucsák, György (2010) On-line sequential bin packing. Journal of Machine Learning Research, 11. pp. 89-109.

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Abstract

We consider a sequential version of the classical bin packing problem in which items are received one by one. Before the size of the next item is revealed, the decision maker needs to decide whether the next item is packed in the currently open bin or the bin is closed and a new bin is opened. If the new item does not fit, it is lost. If a bin is closed, the remaining free space in the bin accounts for a loss. The goal of the decision maker is to minimize the loss accumulated over n periods. We present an algorithm that has a cumulative loss not much larger than any strategy in a finite class of reference strategies for any sequence of items. Special attention is payed to reference strategies that use a fixed threshold at each step to decide whether a new bin is opened. Some positive and negative results are presented for this case.

Item Type:	ISI Article
Uncontrolled Keywords:	bin packing, on-line learning, prediction with expert advice
Subjects:	Q Science > QA Mathematics and Computer Science > QA75 Electronic computers. Computer science / számítástechnika, számítógéptudomány
Depositing User:	Eszter Nagy
Date Deposited:	12 Dec 2012 08:38
Last Modified:	12 Dec 2012 08:38
URI:	https://eprints.sztaki.hu/id/eprint/6354

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