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Cython for Speeding-up Genetic Algorithm

Titre	Cython for Speeding-up Genetic Algorithm
Publication Type	Conference Paper
Year of Publication	2020
Authors	Gad, AF, F. Jarmouni, E
Conference Name	2020 International Conference on Electrical and Information Technologies, ICEIT 2020
Mots-clés	Array elements, Array processing, Data type, Genetic algorithms, High level languages
Abstract	This paper proposes a library for implementing the genetic algorithm using Python mainly in NumPy and speeding-up its execution using Cython. The preliminary Python implementation is inspected for possible optimizations. The 4 main changes include statically defining data types for the NumPy arrays, specifying the data type of the array elements in addition to the number of dimensions, using indexing for looping through the arrays, and finally disabling some unnecessary features in Cython. Using Cython, the NumPy array processing is 1250 times faster than CPython. The Cythonized version of the genetic algorithm is 18 times faster than the Python version. © 2020 IEEE.
URL	https://www.scopus.com/inward/record.uri?eid=2-s2.0-85086899207&doi=10.1109%2fICEIT48248.2020.9113210&partnerID=40&md5=2f21b7d3239af190e4a515e4e967104b
DOI	10.1109/ICEIT48248.2020.9113210