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A New Monarch Butterfly Optimization Algorithm with SA Strategy

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Knowledge Science, Engineering and Management (KSEM 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11776))

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Abstract

Monarch butterfly optimization (MBO) is a newly proposed meta-heuristic algorithm for solving optimization problems. It has been proved experimentally that MBO is superior to the other five state-of-the-art meta-heuristic algorithms on most test problems. This paper presents a new improved MBO algorithm with Simulated Annealing (SA) strategy, in which the SA strategy is involved into the migration operator and butterfly adjusting operator. So the newly proposed algorithm SAMBO not only accepts all the butterfly individuals whose fitness are better than their parents’ but also randomly selects some individuals that are worse than their parents to disturbance the convergence of algorithm. In the final, the experiments are carried out on 14 famous continuous nonlinear functions; the results demonstrate that SAMBO algorithm is significantly better than the original MBO algorithm on most test functions.

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Acknowledgments

This work is supported by the National Natural Science Foundation of China (61373052), the Project of Jilin Provincial Science and Technology Development (20170414004GH).

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Authors and Affiliations

  1. College of Computer Science and Technology, Jilin University, Changchun, 130012, China

    Xitong Wang & Yonggang Zhang

  2. Key Laboratory of Symbolic Computation and Knowledge Engineering, Ministry of Education, Jilin University, Changchun, 130012, China

    Xitong Wang & Yonggang Zhang

  3. The Second Hospital of Jilin University, Changchun, 130041, China

    Xin Tian

Authors
  1. Xitong Wang
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  2. Xin Tian
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  3. Yonggang Zhang
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Corresponding author

Correspondence to Yonggang Zhang .

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Editors and Affiliations

  1. University of Piraeus, Piraeus, Greece

    Christos Douligeris

  2. University of Vienna, Vienna, Austria

    Dimitris Karagiannis

  3. University of Piraeus, Piraeus, Greece

    Dimitris Apostolou

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Wang, X., Tian, X., Zhang, Y. (2019). A New Monarch Butterfly Optimization Algorithm with SA Strategy. In: Douligeris, C., Karagiannis, D., Apostolou, D. (eds) Knowledge Science, Engineering and Management. KSEM 2019. Lecture Notes in Computer Science(), vol 11776. Springer, Cham. https://doi.org/10.1007/978-3-030-29563-9_23

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  • DOI: https://doi.org/10.1007/978-3-030-29563-9_23

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29562-2

  • Online ISBN: 978-3-030-29563-9

  • eBook Packages: Computer ScienceComputer Science (R0)

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