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An efficient local search for partial vertex cover problem

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Abstract

In this paper, an efficient local search framework, namely GRASP-PVC, is proposed to solve the minimum partial vertex cover problem. In order to speed up the convergence, a novel least-cost vertex selecting strategy is applied into GRASP-PVC. As far as we know, no heuristic algorithms have ever been reported to solve this momentous problem and we compare GRASP-PVC with a commercial integer programming solver CPLEX as well as a 2-approximation algorithm on two standard benchmark libraries called DIMACS and BHOSLIB. Experimental results evince that GRASP-PVC finds much better partial vertex covers than CPLEX and the approximation algorithm on most instances. Additional experimental results also confirm the validity of the least-cost vertex selecting strategy.

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Acknowledgements

The authors of this paper wish to extend their sincere gratitude to all anonymous reviewers for their efforts. This work was supported in part by National Natural Science Foundation of China (under Grant Nos. 61503074 and 61402070).

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Authors and Affiliations

  1. School of Computer Science and Information Technology, Northeast Normal University, Changchun, 130117, China

    Yupeng Zhou, Yiyuan Wang, Jian Gao, Na Luo & Jianan Wang

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  1. Yupeng Zhou
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  2. Yiyuan Wang
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  3. Jian Gao
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  4. Na Luo
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  5. Jianan Wang
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Correspondence to Jianan Wang.

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Zhou, Y., Wang, Y., Gao, J. et al. An efficient local search for partial vertex cover problem. Neural Comput & Applic 30, 2245–2256 (2018). https://doi.org/10.1007/s00521-016-2800-z

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