Machine learningSwarm Intelligence

Jellyfish Search Optimizer

The Jellyfish Search Optimizer (JSO) is a biologically-inspired metaheuristic algorithm introduced by Shi et al. in 2022, based on the movement and foraging behavior of jellyfish in ocean environments. Jellyfish exhibit two distinct behaviors: passive drifting with ocean currents (exploration) and active swimming toward food sources (exploitation). JSO captures these behaviors to create an effective balance between global search and local refinement.

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Sources

  1. Shi, X., Sun, Y., Zhan, Z. H., Yuen, K. F., & Zhang, J. (2022). Jellyfish search optimizer: A new bio-inspired metaheuristic algorithm for solving optimization tasks. Neural Computing and Applications, 34(10), 7651-7673. DOI: 10.1007/s00521-022-07004-y

Related methods

ScholarGateJellyfish Search Optimizer (Jellyfish Search Optimizer). Retrieved 2026-06-04 from https://scholargate.app/en/optimization/jellyfish-search-optimizer