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Python package for AEFA: Artificial electric field algorithm for global optimization
AEFA is a Python library for AEFA: Artificial electric field algorithm, a novel algorithm for solving non-linear optimization problems. The details of the algorithm can be found here at: https://medium.com/artifical-mind/artificial-electric-field-algorithm-for-optimization-fb6f57f413b4 You may access the paper for the same at http://www.sciencedirect.com/science/article/pii/S2210650218305030
Use the package manager pip to install aefaalgo.
pip install aefaalgo
from aefaalgo.aefa_optimize import aefa
# returns optimum fitness value and space coordinates
aefa().optimize(N, max_iter, func_num)
Keyword arguments:
N: number of particles in search space
max_iter: number of iterations
func_num: Specifies the function to be optimized
Optional Keyword Arguments:
tag: specifies whether we want maxima or minima.
0 by default for maximization. Specify tag=1 for minimization.
Rpower: exponent for the normalized distance between the particles.
Default value 1
FCheck: This factor ensures that only 2-6% charges apply force to others in the last iterations.
Set to True by default.
show_plot: True if you want to visualize convergence to the optimum, False otherwise and default.
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Download counts and popularity will appear here as the collector receives them.
| Version | Published | Direct dependencies | Open version |
|---|---|---|---|
| 0.0.5 | 21 Nov 2021 | 2 |
This describes our collected data; it is not a security assessment.
Observed since 20 Oct, 20:11 UTC
No superseded metadata states collected. Unchanged observations do not create new revisions.
package:ccf3cd8ebf69f28815c057204df240962757283a6c5d30581e27e14c2c5469c4