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A Comprehensive Survey on Squirrel Search Algorithm

Author

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  • Hao Lin

    (College of Intelligent Science and Technology, Inner Mongolia University of Technology, China)

  • Leixiao Li

    (College of Intelligent Science and Technology, Inner Mongolia University of Technology, China)

Abstract

The Squirrel Search Algorithm (SSA) has garnered considerable attention from the academic community and is increasingly applied across multiple disciplines to tackle a variety of optimization challenges since 2019. Inspired by the dynamic foraging behavior of southern flying squirrels, the SSA mimics their energy-efficient gliding locomotion—a special adaptive strategy that enables these small mammals to traverse large distances with minimal effort. This study offers a comprehensive analysis of the original SSA, along with its modifications, hybridizations, and variants. Furthermore, this study elucidated the practical applications of SSA across various engineering disciplines and incorporated analyses of studies demonstrating suboptimal SSA performance. Finally, the authors discuss future research directions to further enhance the SSA's performance.

Suggested Citation

  • Hao Lin & Leixiao Li, 2026. "A Comprehensive Survey on Squirrel Search Algorithm," International Journal of Swarm Intelligence Research (IJSIR), IGI Global Scientific Publishing, vol. 17(1), pages 1-33, January.
    • Handle: RePEc:igg:jsir00:v:17:y:2026:i:1:p:1-33
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