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A parallel variable neighborhood search for solving covering salesman problem

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Abstract

Covering salesman problem (CSP) is to construct a minimum length Hamiltonian cycle over a subset of vertices, in which the vertices not visited on the cycle must be covered by at least one visited vertex. In this paper, the CSP is reformulated as a bilevel CSP (BCSP) with a leader and a follower sub-problem. Two parallel variable neighborhood search (PVNS) heuristics, namely, synchronous “master–slave” PVNS and asynchronous cooperative PVNS, are proposed to solve the BCSP. To test the proposed algorithms, extensive computational experiments on the benchmark instances are performed, and the results indicate the effectiveness of the proposed approaches.

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Acknowledgements

This work was supported by the Ministry of Chinese Education, Humanities and Social Sciences under Grant 17YJA630037 and the Project of Graduate Teaching Quality in Hefei University of Technology (Grant No. 110-4116000050).

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Authors and Affiliations

  1. School of Management, University of Science and Technology of China, Hefei, 230026, Anhui, People’s Republic of China

    Xiaoning Zang & Bin Ding

  2. School of Management, Hefei University of Technology, Hefei, 230009, Anhui, People’s Republic of China

    Li Jiang

  3. Key Laboratory of Process Optimization and Intelligent Decision-Making, Ministry of Education, Hefei, 230009, Anhui, People’s Republic of China

    Li Jiang

  4. Université Polytechnique Hauts-De-France (UPHF)/LAMIH CNRS UMR 8201, Valenciennes Cedex 9, France

    Mustapha Ratli

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  1. Xiaoning Zang
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  2. Li Jiang
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  3. Mustapha Ratli
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  4. Bin Ding
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Correspondence to Li Jiang.

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Zang, X., Jiang, L., Ratli, M. et al. A parallel variable neighborhood search for solving covering salesman problem. Optim Lett 16, 175–190 (2022). https://doi.org/10.1007/s11590-020-01642-8

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  • DOI: https://doi.org/10.1007/s11590-020-01642-8

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