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Artificial Hummingbird Algorithm

version 1.0.1 (13.5 KB) by W. Zhao
Artificial Hummingbird Algorithm (AHA): A novel bio-inspired optimization algorithm

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Updated 28 Oct 2021

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The Artificial Hummingbird Algorithm (AHA) is inspired by the special flight skills and intelligent foraging strategies of hummingbirds in nature. Three foraging strategies of hummingbirds, including the guided foraging, territorial foraging, and migrating foraging, are implemented. Moreover, three kinds of flight skills utilized in the foraging strategies such as the axial, diagonal, and omnidirectional flights, are modeled. Specially, a visit table mimicking the supernormal memory ability of hummingbirds is constructed to guide the hummingbirds in the algorithm for performing the global optimization.
The performance of AHA is tested on 23 benchmark functions and 50 benchmark functions, demonstrating its optimization ability in solving global optimization problems.
The MATLAB m-files of the Artificial Hummingbird Algorithm (AHA) can be downloaded from the following link, in which two sets of benchmarks, including 23 functions and 50 functions, are used in the optimizer.
Main paper: W. Zhao, L. Wang and S. Mirjalili, Artificial hummingbird algorithm: A new bio-inspired optimizer with its engineering applications, Computer Methods in Applied Mechanics and Engineering (2021) 114194, https://doi.org/10.1016/j.cma.2021.114194.

Cite As

W. Zhao (2021). Artificial Hummingbird Algorithm (https://www.mathworks.com/matlabcentral/fileexchange/101133-artificial-hummingbird-algorithm), MATLAB Central File Exchange. Retrieved .

MATLAB Release Compatibility
Created with R2016a
Compatible with any release
Platform Compatibility
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AHA for 23 benchmark functions

AHA for 50 benchmark functions