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An improved ant-based heuristic approach for solving the longest cycle problem in large-scale complex networks

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Abstract

The longest cycle problem (LCP) has a crucial significance in graph theory and has a wide range of applications in the real-world. Although some excellent LCP solvers have been proposed in recent years, there is still a need for more efficient algorithms to solve the LCP of large-scale real-world complex networks. This paper proposed a fast algorithm ANTH-PDLS (ant heuristic with path disturbance local search) for the LCP. In ANTH-PDLS, two reduction strategies are proposed to reduce the scale of the networks, and a path disturbance strategy is proposed to expand the search ability. Experiments with randomly generated instances and real-world instances show that these strategies are effective. The average solution time of ANTH-PDLS on 21 real-world instances is only 15.5% of the existing excellent algorithms.

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Authors and Affiliations

  1. College of Computer Science, Chongqing University, Chongqing, 400044, China

    Ping Guo & Yicheng Jiang

  2. Chongqing Key Laboratory of Software Theory and Technology, Chongqing, 400044, China

    Ping Guo

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  1. Ping Guo
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  2. Yicheng Jiang
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Correspondence to Ping Guo.

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Guo, P., Jiang, Y. An improved ant-based heuristic approach for solving the longest cycle problem in large-scale complex networks. J Supercomput 78, 14164–14190 (2022). https://doi.org/10.1007/s11227-022-04409-3

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