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Self-organizing hierarchical monkey algorithm with time-varying parameter

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Abstract

This paper proposes a self-organizing hierarchical monkey algorithm (SHMA) with a time-varying parameter to improve the performance of the original monkey algorithm (MA). In the proposed SHMA, we adopt a hierarchical structure to organize the climb, watch, and somersault operations and apply a self-organizing mechanism to coordinate these operations. Moreover, a time-varying parameter is employed to adjust the exploration ability and exploitation ability during the optimization process. The SHMA also applies the fitness information of solutions to guide the optimization process and introduces a selection operator, a fitness-based replacement operator, and a repulsion operator into the climb, watch and somersault operations, respectively. To investigate the performance of the SHMA, we compare it with eight different metaheuristic algorithms on 30 benchmark problems and four real-world optimization problems. The simulation results show that the SHMA exhibits better overall performance than the eight compared algorithms.

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Acknowledgements

The authors wish to thank the anonymous reviewers, whose valuable comments lead to an improved version of the paper. This work was supported by the National Natural Science Foundation of China under Grant Nos.71701187, 71771166 and 71771165, and Research Project of Zhejiang Education Department under Grant No. Y201738184 and High Performance Computing Center of Tianjin University, China.

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Authors and Affiliations

  1. College of Economic and Management, Zhejiang Normal University, Jinhua, 321004, China

    Gaoji Sun

  2. Institute of Systems Engineering, Tianjin University, Tianjin, 300072, China

    Yanfei Lan & Ruiqing Zhao

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  1. Gaoji Sun
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  2. Yanfei Lan
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  3. Ruiqing Zhao
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Correspondence to Gaoji Sun or Yanfei Lan.

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Sun, G., Lan, Y. & Zhao, R. Self-organizing hierarchical monkey algorithm with time-varying parameter. Neural Comput & Applic 31, 3245–3263 (2019). https://doi.org/10.1007/s00521-017-3265-4

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