Greylag Goose Optimization (GGO) algorithm

Version 1.0.0 (1.85 KB) by praveen kumar
sphere function is tested
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Updated 13 Apr 2024

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The Greylag Goose Optimization (GGO) algorithm is a metaheuristic optimization algorithm inspired by the foraging behavior of the greylag goose. It was proposed by Ramalingam et al. in 2018. The algorithm mimics the movement patterns of the greylag goose during foraging, including exploration, exploitation, and flocking behavior.

Cite As

praveen kumar (2026). Greylag Goose Optimization (GGO) algorithm (https://uk.mathworks.com/matlabcentral/fileexchange/163321-greylag-goose-optimization-ggo-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2022b
Compatible with any release
Platform Compatibility
Windows macOS Linux
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Version Published Release Notes
1.0.0