Prairie Dog Optimization Algorithm

Prairie Dog Optimization (PDO) is a new population-based metaheuristic algorithm for solving numerical optimization problems.

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PDO is a new nature-inspired metaheuristic that mimics the behaviour of the prairie dogs in their natural habitat. The proposed algorithm uses four prairie dog activities to achieve the two common optimization phases, exploration and exploitation. The prairie dogs' foraging and burrow build activities are used to provide exploratory behaviour for the PDO algorithm.

Cite As

Absalom E. Ezugwu, Jeffrey O. Agushaka, Laith Abualigah, Seyedali Mirjalili, Amir H Gandomi, “Prairie Dog Optimization Algorithm” Neural Computing and Applications, 2022. DOI: 10.1007/s00521-022-07530-9

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General Information

MATLAB Release Compatibility

  • Compatible with any release

Platform Compatibility

  • Windows
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  • Linux
Version Published Release Notes Action
1.2.0

Citation for this work is now available

1.1.0

Updated Version

1.0.0