JISE


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Journal of Information Science and Engineering, Vol. 36 No. 2, pp. 231-241


Evaluation of Genetic Algorithm Optimization in Machine Learning


DHEYAA SHAHEED AL-AZZAWI
Department of Computer
College of Computer Science and Information Technology
Wasit University
Wasit, 52001 Iraq
E-mail: dalazzawi@uowasit.edu.iq​


The manuscript is presenting the usage scenarios of Genetic Algorithm is one of the high performance algorithms for the engineering optimization. The aim of this paper is to present the effectual implementation with the prominent evolutionary computation method of genetic algorithm for the data analytics and in specific usage towards the multiprocessor scheduling approach. The presented algorithm is giving the superior outcomes on the assorted parameters so that the concrete and tangible results from genetic algorithm can be presented. The traditional or previous methods were making use of greedy based approach and thereby the results were not effective that motivated and prompted to work on the genetic algorithm based optimization approach. The implementation scenarios are simulated in MATLAB as well as Java based development libraries and found the outcome quite effective and valuable in terms of optimization.


Keywords: genetic algorithm, engineering optimization, search based optimization, data analysis, artificial intelligence

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