The Artificial H
ummingbird
A
lgorithm (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,
t
hree kinds of flight skills utilized in
the
foraging strategies
such as
the
axial, diagonal, and omnidirectional flights, are modeled.
Specially,
a visit table
模仿
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
力学与工程(2021)114194,https://doi.org/10.1016/j.cma.2021.114194。