Abstract
We introduce a new online algorithm for the multiselection problem which performs a sequence of selection queries on a given unsorted array. We show that our online algorithm is 1-competitive in terms of data comparisons. In particular, we match the bounds (up to lower order terms) from the optimal offline algorithm proposed by Kaligosi et al. [ICALP 2005].
We provide experimental results comparing online and offline algorithms. These experiments show that our online algorithms require fewer comparisons than the best-known offline algorithms. Interestingly, our experiments suggest that our optimal online algorithm (when used to sort the array) requires fewer comparisons than both quicksort and mergesort.
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Barbay, J., Gupta, A., Jo, S., Rao, S.S., Sorenson, J. (2013). Theory and Implementation of Online Multiselection Algorithms. In: Bodlaender, H.L., Italiano, G.F. (eds) Algorithms – ESA 2013. ESA 2013. Lecture Notes in Computer Science, vol 8125. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-40450-4_10
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DOI: https://doi.org/10.1007/978-3-642-40450-4_10
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