Greylag Goose Optimization (GGO) algorithm

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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://in.mathworks.com/matlabcentral/fileexchange/163321-greylag-goose-optimization-ggo-algorithm), MATLAB Central File Exchange. Retrieved .

General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
  • macOS
  • Linux
Version Published Release Notes Action
1.0.0