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Quickly Finding the Smallest Numerical Subset with Its Sum above a Threshold

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Abstract

Given a set of numerical values and a threshold, finding the minimum subset from the set such that its sum is not less than the threshold value, is termed as SelectSum problem which is widely applicable in data compression and image processing. In this article, we provide two new linear-time algorithms for the problem. Different from the current approaches that directly calling the Selection algorithms for partitioning on median elements, our proposed algorithms embed the Selection process and use cheap pivot elements for partitioning. The experimental tests indicate these two new algorithms are significant faster than the current existing algorithms on larger data sets.

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Acknowledgements

The authors acknowledge National Science Foundation Project of Zhejiang of China (Grant: LY16G010010, LY18F020001), and Ningbo Innovative Team: The intelligent big data engineering application for life and health (Grant: 2016C11024).

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Authors and Affiliations

  1. The Sino-Aus Joint Center for Social Computing and Data Management, Ningbo Institute of Technology, Zhejiang University (NIT), Ningbo, China

    Libo Xu, Chaoyi Pang & Xingsen Li

  2. Hebei University of Economics and Business, Shijiazhuang, Hebei, China

    Chaoyi Pang

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  1. Libo Xu
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  2. Chaoyi Pang
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  3. Xingsen Li
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Correspondence to Chaoyi Pang.

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Xu, L., Pang, C. & Li, X. Quickly Finding the Smallest Numerical Subset with Its Sum above a Threshold. Wireless Pers Commun 103, 427–436 (2018). https://doi.org/10.1007/s11277-018-5452-8

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  • DOI: https://doi.org/10.1007/s11277-018-5452-8

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