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The octopus–reef fish cooperative hunting optimizer: an efficient bio-inspired algorithm for global optimization and engineering applications
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DOI：10.1007/s00521-026-12341-3.png)
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Abstract
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This paper introduces a novel bio-inspired metaheuristic algorithm named the Octopus-Reef Fish Cooperative Hunting Optimizer (ORCHO). It draws inspiration from the interspecies cooperative hunting behavior observed between octopuses and reef fish within coral reef ecosystems. This symbiotic strategy, which involves communication, role division, and coordinated actions to drive and capture prey, offers a novel paradigm for optimization problems. ORCHO mathematically models these behaviors to achieve an efficient balance between global exploration and local exploitation. ORCHO was rigorously evaluated on comprehensive benchmark suites, including CEC-2017 and CEC-2022, and its performance was validated through statistical tests against state-of-the-art algorithms. Furthermore, its practical efficacy was validated through testing on real-world engineering optimization problems from CEC-2020, where its performance rivaled that of leading algorithms recognized at CEC-2020. Notably, ORCHO also demonstrates outstanding performance on the 10-dimensional CEC2017 test set, comparable to CEC championship algorithms such as LSHADE-SPACMA and L-SRTDE. Source code of ORCHO is publicly available at https://github.com/wangzhanjiang001/ORCHO .
Keywords:
Octopus-Reef fish Cooperative Hunting Optimizer (ORCHO)
Swarm intelligence
Global optimization
Real-world engineering problems
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4.5
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3.2W
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