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Investigation and Optimization of Scheduling System in Sohar University using Genetic Algorithm (GA)

by Maryam Alwashahi
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 126 - Number 11
Year of Publication: 2015
Authors: Maryam Alwashahi
10.5120/ijca2015906216

Maryam Alwashahi . Investigation and Optimization of Scheduling System in Sohar University using Genetic Algorithm (GA). International Journal of Computer Applications. 126, 11 ( September 2015), 11-15. DOI=10.5120/ijca2015906216

@article{ 10.5120/ijca2015906216,
author = { Maryam Alwashahi },
title = { Investigation and Optimization of Scheduling System in Sohar University using Genetic Algorithm (GA) },
journal = { International Journal of Computer Applications },
issue_date = { September 2015 },
volume = { 126 },
number = { 11 },
month = { September },
year = { 2015 },
issn = { 0975-8887 },
pages = { 11-15 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume126/number11/22595-2015906216/ },
doi = { 10.5120/ijca2015906216 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:17:10.490261+05:30
%A Maryam Alwashahi
%T Investigation and Optimization of Scheduling System in Sohar University using Genetic Algorithm (GA)
%J International Journal of Computer Applications
%@ 0975-8887
%V 126
%N 11
%P 11-15
%D 2015
%I Foundation of Computer Science (FCS), NY, USA
Abstract

This paper presents the results of an investigation, and optimization of scheduling system in Sohar University (as a case study) using the genetic algorithm (GA). GA techniques are useful for solving real-world scheduling problem such as timetable which is a complex work and usually done manually. This work focuses on scheduling courses timetable to allocate events (time, subject, and lecturer) in an appropriate way by using the available resource and assists to avoid conflicts. The algorithms explored different operator of GA such as crossover, mutation, and selection mechanism that’s applied to set of chromosomes. The testing has been produced using different parameters of population size, crossover, and mutation probability. Two point crossovers implemented to the timetable to obtain the optimal solution using various probabilities of crossover. The result shows the rate of crossover and mutation equal to 100 performed best optimal solutions. This paper recommended to enhance the fitness function and used different selection mechanism to the algorithm.

References
  1. Schaerf , A., “A Survey of Automated Timetabling” , Artificial Intelligence review, 1999, [Online] Available http://www.diegm.uniud.it/satt/papers/Scha99.pdf
  2. Sigl Branimir, Marin Golub, Vedran Mornar, “Solving Timetable Scheduling Problem by Using Genetic Algorithms”,
  3. Yang and Petrovic, “A Novel Similarity Measure for Heuristic Selection in Examination”, PATAT 2004 Proceedings of the 5th International Conference on the Practice and Theory of Automated Timetabling.
  4. Sandhu Kuldeep Singh, “Automating Class Schedule Generation in the context of a University Timetabling Information System”, Thesis submitted to School of Management, Nathan campus, Griffith University, 2001.
  5. Ehrgott M and Gandibleux X, “ A Survey and Annotated Bibliography of Multiobjective Combinatorial Optimization”, OR Spectrum, 2004.
  6. B. Szpigel, “Optimal train scheduling on a single track railway”, Proceedings of IFORS Conference on Operational Research’72, 343–352.
  7. R.Sivaraj, “A REVIEW OF SELECTION METHODS IN GENETIC ALGORITHMS”, International Journal of Engineering Science and Technology(IJEST), vol. 3, MAY 2001, p. 3792.
  8. José-Revuelta, L.M.S.,”A Hybrid GA-TS Technique with Dynamic Operators and its Application to Channel Equalization and Fiber Tracking”, [Online], Available: http://cdn.intechweb.org/pdfs/4594.pdf [01 September 2013.
  9. K. F. Man, K. S. Tang, and S. Kwong, “ Genetic Algorithms: Concepts and Applications”, IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, VOL. 43, NO. 5, OCTOBER 1996.
  10. Ehsan Alirezaei, Z.V.a.M.G.-G., “Parallel Hybrid Meta Heuristic Algorithm for University Course Timetabling Problem (PHACT)”, ‘20th Iranian Conference on Electrical Engineering, (ICEE2012)’. held May 15-17,2012 at Tehran.Iran: IEEE,673-678.
  11. Chinnasri, W., Krootjohn, S. ,Sureerattanan, N. , “Performance comparison of Genetic Algorithm's crossover operators on University Course Timetabling Problem”,’In anon .ED.Computing Technology and Information Management (ICCM), 2012 8th International Conference  ‘ held 24-26 April 2012 at Seoul, Korea (South) . King Mongkut''s Univ. Of Technol: IEEE, 781-786.
  12. Lukas, S., Aribowo, A., Muchri, M.,"Genetic algorithm and heuristic search for solving timetable problem case study: Universities Pelita Harapan timetable",  Applications of Digital Information and Web Technologies, 2009. ICADIWT '09. Second International Conference on the , vol., no., pp.629,633, 4-6 Aug. 2009 doi: 10.1109/ICADIWT.2009.5273979
Index Terms

Computer Science
Information Sciences

Keywords

Timetable problems Genetic Algorithm (GA) Non-deterministic Polynomial (NP)

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