basic_customized_example

Complexity

Total Complexity

0

Size/Duplication

Total Lines	26
Duplicated Lines	0 %

Importance

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0

# This is temporary fix to import module from parent folder
# It will be removed when package is published on PyPI
import sys
sys.path.append('../')
# End of fix

from NiaPy.algorithms.basic import GreyWolfOptimizer
from NiaPy.benchmarks import Pinter

# initialize Pinter benchamrk with custom bound
pinterCustom = Pinter(-5, 5)

# we will run 10 repetitions of Grey Wolf Optimizer against Pinter benchmark function
for i in range(10):
    # first parameter takes dimension of problem
    # second parameter is population size
    # third parameter takes the number of function evaluations
    # fourth parameter is benchmark function 
    algorithm = GreyWolfOptimizer(10, 20 , 10000, pinterCustom)

    # running algorithm returns best found minimum
    best = algorithm.run()

    # printing best minimum
    print(best)