Prairie Dog Optimization Algorithm
Version 1.2.0 (7,21 KB) von
Absalom Ezugwu
Prairie Dog Optimization (PDO) is a new population-based metaheuristic algorithm for solving numerical optimization problems.
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.
Zitieren als
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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PDO
| Version | Veröffentlicht | Versionshinweise | |
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| 1.2.0 | Citation for this work is now available |
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| 1.1.0 | Updated Version |
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| 1.0.0 |
