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A rough set method for the unicost set covering problem

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Abstract

In this paper, we aim to provide a rough set method to deal with a class of set covering problem called the unicost set covering problem, which is a well-known problem in binary optimization. Firstly, by constructing a Multi-Relation Granular Computing (GrC) model of a given unicost set covering problem, the problem can be equivalently converted to the knowledge reduction problem in rough set theory. Thus, various kinds of efficient knowledge reduction methods in rough set theory can be used to solve the unicost set covering problem. Secondly, a commonly used reduction algorithm based on information entropy is proposed to compute a local minimum of the unicost set covering problem. Finally, the feasibility and efficiency of the proposed algorithm is examined by an example.

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Acknowledgments

The authors thank the anonymous referees for their valuable comments and suggestions. This work is supported by grants from National Natural Science Foundation of China under Grant (Nos. 61379021, 11301367, 11061004, 61303131) and the Department of Education of Fujian Province (Nos. JA13202, JA13198, JK2013027, JK2014028, 2015J05011).

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Authors and Affiliations

  1. School of Computer Science, Minnan Normal University, Zhangzhou, 363000, China

    Qingyuan Xu & Yaojin Lin

  2. School of Mathematics and statistics, Minnan Normal University, Zhangzhou, 363000, China

    Anhui Tan

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  1. Qingyuan Xu
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  2. Anhui Tan
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  3. Yaojin Lin
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Correspondence to Qingyuan Xu or Anhui Tan.

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Xu, Q., Tan, A. & Lin, Y. A rough set method for the unicost set covering problem. Int. J. Mach. Learn. & Cyber. 8, 781–792 (2017). https://doi.org/10.1007/s13042-015-0365-2

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