https://github.com/buma/batalgorithm

https://github.com/buma/batalgorithm

Last synced: about 2 months ago
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• Host: GitHub
• URL: https://github.com/buma/batalgorithm
• Owner: buma
• License: mit
• Created: 2015-09-18T17:42:34.000Z (over 9 years ago)
• Default Branch: master
• Last Pushed: 2020-10-19T06:04:04.000Z (about 4 years ago)
• Last Synced: 2024-09-14T22:02:44.467Z (4 months ago)
• Language: Python
• Size: 8.79 KB
• Stars: 37
• Watchers: 3
• Forks: 16
• Open Issues: 3
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

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README

        
# Bat Algorithm in Python

## Objective

The main objective is to create an implementation of bat algorithm in Python programming language.

## Installation

    pip install BatAlgorithm

### Example

The following example presents a simple use of bat algorithm. `Fun()` denotes the objective function that may be changed by the user. Control parameters should be defined within `BatAlgorithm()` constructor. Order of parameters is as

follows: `BatAlgorithm(D, NP, N_Gen, A, r, Qmin, Qmax, Lower, Upper, function)` where:

- `D`  denotes dimension of the problem,

- `NP` denotes population size,

- `N_Gen`  denotes number of generations (iterations),

- `A` parameter denotes loudness,

- `r` parameter denotes pulse rate,

- `Qmin` parameter denotes frequency minimum,

- `Qmax` parameter denotes frequency maximum,

- `Lower` denotes lower bound,

- `Upper` denotes upper bound and

- `function` passes objective function.

## CODE EXAMPLE:

```python

import random

from BatAlgorithm import *

def Fun(D, sol):

    val = 0.0

    for i in range(D):

        val = val + sol[i] * sol[i]

    return val

# For reproducive results

#random.seed(5)

for i in range(10):

    Algorithm = BatAlgorithm(10, 40, 1000, 0.5, 0.5, 0.0, 2.0, -10.0, 10.0, Fun)

    Algorithm.move_bat()

```

## Bugs

Bugs and extension should be send via Github.

## Authors

Iztok Fister Jr. and Marko Burjek

## References

Yang, X.-S. "A new metaheuristic bat-inspired algorithm." Nature inspired cooperative strategies for optimization (NICSO 2010). Springer

Berlin Heidelberg, 2010. 65-74.

Fister, I. Jr., Fister, I., Yang, X.-S., Fong, S., Zhuang, Y. "Bat algorithm: Recent advances." IEEE 15th International Symposium on Computational Intelligence and Informatics (CINTI), IEEE, 2014. 163-167.