OPTIMIZATION ALGORITHMS OVERVIEW FOR COURSESCHEDULING

Today we have a lot of optimization algorithms that can be used for course scheduling, but the main question is which of them fulfills our requirements better and what are the advantages of one from the others. Since course scheduling is an NP-problem, in this article we will look at a few of algorithms that are used to solve different problems and have proved themselves only on the best side and compare their main advantages. When comparing, we will rely not only on the accuracy of the results, but also on the speed of solving complex problems, and on solving complex conditions.

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Publication Details

Journal
Suleyman Demirel University Bulletin Natural and Technical Sciences
Published
2024-10-16
DOI
https://doi.org/10.47344/sdubnts.v55i2.540
Primary Topic
Experimental Learning in Engineering
Type
article
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article

OPTIMIZATION ALGORITHMS OVERVIEW FOR COURSESCHEDULING

Rassim Suliyev, M. Zhuniskhanov
Suleyman Demirel University Bulletin Natural and Technical Sciences
Experimental Learning in Engineering
article

OPTIMIZATION ALGORITHMS OVERVIEW FOR COURSESCHEDULING

Rassim Suliyev, M. Zhuniskhanov
article en

Abstract

Today we have a lot of optimization algorithms that can be used for course scheduling, but the main question is which of them fulfills our requirements better and what are the advantages of one from the others. Since course scheduling is an NP-problem, in this article we will look at a few of algorithms that are used to solve different problems and have proved themselves only on the best side and compare their main advantages. When comparing, we will rely not only on the accuracy of the results, but also on the speed of solving complex problems, and on solving complex conditions.

Suleyman Demirel University Bulletin Natural and Technical SciencesVol. 55(2)
Openalex Percentile: Top 61%
Experimental Learning in Engineering
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