Abstract
Motivated by recent best case analyses for some sorting algorithms and based on the type of complexity we partition the algorithms into two classes: homogeneous and non-homogeneous algorithms.1 Although both classes contain algorithms with worst and best cases, homogeneous algorithms behave uniformly on all instances. This partition clarifies in a completely mathematical way the previously mentioned terms and reveals that in classifying an algorithm as homogeneous or not best case analysis is equally important with worst case analysis.
This paper was also presented at local proceedings of PCI’09 [Paparrizos, Homogeneous and Non-Homogeneous Algorithms (2009)].
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Acknowledgements
We thank an anonymous referee for useful suggestions and for bringing to our attention the reference [17].
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Paparrizos, I. (2013). Homogeneous and Non-homogeneous Algorithms. In: Migdalas, A., Sifaleras, A., Georgiadis, C., Papathanasiou, J., Stiakakis, E. (eds) Optimization Theory, Decision Making, and Operations Research Applications. Springer Proceedings in Mathematics & Statistics, vol 31. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-5134-1_17
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