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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:

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.

Metadata

Release files for BatAlgorithm 0.3.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for BatAlgorithm 0.3.1
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Release files / BatAlgorithm-0.3.1.tar.gz

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