AEFA
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
Installation
Use the package manager pip to install aefaalgo.
pip install aefaalgo
Usage
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.
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
Release files for aefaalgo 0.0.5
For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.
Source distribution (sdist)
| File | Size | Uploaded | |
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| aefaalgo-0.0.5.tar.gz | 5.9 kB | Details |
Built distribution (wheel)
| File | Interpreter | ABI | Platform | Reset |
|---|---|---|---|---|
| aefaalgo-0.0.5-py3-none-any.whl | Python 3 | none | any | Details |
Total release size: 12.7 kB
Release files / aefaalgo-0.0.5.tar.gz
| Download URL | aefaalgo-0.0.5.tar.gz |
|---|---|
| Size | 5.9 kB |
| Tags | Source |
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Release files / aefaalgo-0.0.5-py3-none-any.whl
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| Tags | Python 3 |
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