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Spider Monkey Optimization: a survey

Author

Listed:
  • Vani Agrawal

    (Jiwaji University)

  • Ratika Rastogi

    (Jiwaji University)

  • D. C. Tiwari

    (Jiwaji University)

Abstract

Algorithms inspired by the intelligent social behavior of simple agents have become popular among the researchers in the recent years. These algorithms are able to find the solution of those real-world optimization problems, which otherwise cannot be solved easily by deterministic techniques. Spider Monkey Optimization (SMO) is one such algorithm which is inspired by the intelligent behavior of spider monkeys. SMO and its variants have been successful and effective in dealing with complex real world optimization problems due to its high efficacy. This paper presents an intense review of SMO, its variants, applications and relative performance with other algorithms .

Suggested Citation

  • Vani Agrawal & Ratika Rastogi & D. C. Tiwari, 2018. "Spider Monkey Optimization: a survey," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(4), pages 929-941, August.
    • Handle: RePEc:spr:ijsaem:v:9:y:2018:i:4:d:10.1007_s13198-017-0685-6
    DOI: 10.1007/s13198-017-0685-6
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    References listed on IDEAS

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    1. R. Venkata Rao, 2007. "Vendor selection in a supply chain using analytic hierarchy process and genetic algorithm methods," International Journal of Services and Operations Management, Inderscience Enterprises Ltd, vol. 3(3), pages 355-369.
    2. Ajay Sharma & Harish Sharma & Annapurna Bhargava & Nirmala Sharma, 2017. "Power law-based local search in spider monkey optimisation for lower order system modelling," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(1), pages 150-160, January.
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    Cited by:

    1. Khairul Eahsun Fahim & Liyanage C. De Silva & Fayaz Hussain & Hayati Yassin, 2023. "A State-of-the-Art Review on Optimization Methods and Techniques for Economic Load Dispatch with Photovoltaic Systems: Progress, Challenges, and Recommendations," Sustainability, MDPI, vol. 15(15), pages 1-29, August.

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