Intership supervisor selection using genetic algorithms

Supervisor selection is a frequently task found among the committee or management group in several organization. The selection tasks will be prepared at accordance times with the proper listing at particular event or duration. Indirectly, the organization of committee or management group will be mor...

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Main Author:	Karim, Junaida
Format:	Thesis
Language:	English English
Published:	2015
Subjects:	H Social Sciences (General) HF Commerce
Online Access:	http://eprints.utem.edu.my/id/eprint/15883/1/INTERNSHIP%20SUPERVISOR%20SELECTION%20USING%20GENETIC%20ALGORITHMS%20%2824%20pgs%29.pdf http://eprints.utem.edu.my/id/eprint/15883/2/Intership%20supervisor%20selection%20using%20genetic%20algorithms.pdf
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id	my-utem-ep.15883
record_format	uketd_dc
institution	Universiti Teknikal Malaysia Melaka
collection	UTeM Repository
language	English English
advisor	Basiron, Halizah
topic	H Social Sciences (General) HF Commerce
spellingShingle	H Social Sciences (General) HF Commerce Karim, Junaida Intership supervisor selection using genetic algorithms
description	Supervisor selection is a frequently task found among the committee or management group in several organization. The selection tasks will be prepared at accordance times with the proper listing at particular event or duration. Indirectly, the organization of committee or management group will be more efficient; well organized and manageable. In this study, Fakulti Teknologi Maklumat Dan Komunikasi (FTMK) at Universiti Teknikal Melaka Malaysia (UTeM) was chosen to be the case study for the researcher to test the genetic algorithm based on the criteria used by the faculty. From the investigation the internship supervisor selection can be defined as forming the allocation supervisor to the internship student from the FTMK with certain constraints to be satisfied. By using genetic algorithm approach, the priority factors for the assigning faculty supervisor to internship student has been identified and also development model of selection has been done to fulfill the criteria for the selection specified by the FTMK. Experimental results from the model selection output can used to verify with an actual data on selection of internship supervisor in FTMK, UTeM.
format	Thesis
qualification_name	Master of Philosophy (M.Phil.)
qualification_level	Master's degree
author	Karim, Junaida
author_facet	Karim, Junaida
author_sort	Karim, Junaida
title	Intership supervisor selection using genetic algorithms
title_short	Intership supervisor selection using genetic algorithms
title_full	Intership supervisor selection using genetic algorithms
title_fullStr	Intership supervisor selection using genetic algorithms
title_full_unstemmed	Intership supervisor selection using genetic algorithms
title_sort	intership supervisor selection using genetic algorithms
granting_institution	Universiti Teknikal Malaysia Melaka
granting_department	Faculty of Information and Communication Technology
publishDate	2015
url	http://eprints.utem.edu.my/id/eprint/15883/1/INTERNSHIP%20SUPERVISOR%20SELECTION%20USING%20GENETIC%20ALGORITHMS%20%2824%20pgs%29.pdf http://eprints.utem.edu.my/id/eprint/15883/2/Intership%20supervisor%20selection%20using%20genetic%20algorithms.pdf
_version_	1747833880299175936
spelling	my-utem-ep.158832022-04-19T10:02:29Z Intership supervisor selection using genetic algorithms 2015 Karim, Junaida H Social Sciences (General) HF Commerce Supervisor selection is a frequently task found among the committee or management group in several organization. The selection tasks will be prepared at accordance times with the proper listing at particular event or duration. Indirectly, the organization of committee or management group will be more efficient; well organized and manageable. In this study, Fakulti Teknologi Maklumat Dan Komunikasi (FTMK) at Universiti Teknikal Melaka Malaysia (UTeM) was chosen to be the case study for the researcher to test the genetic algorithm based on the criteria used by the faculty. From the investigation the internship supervisor selection can be defined as forming the allocation supervisor to the internship student from the FTMK with certain constraints to be satisfied. By using genetic algorithm approach, the priority factors for the assigning faculty supervisor to internship student has been identified and also development model of selection has been done to fulfill the criteria for the selection specified by the FTMK. Experimental results from the model selection output can used to verify with an actual data on selection of internship supervisor in FTMK, UTeM. 2015 Thesis http://eprints.utem.edu.my/id/eprint/15883/ http://eprints.utem.edu.my/id/eprint/15883/1/INTERNSHIP%20SUPERVISOR%20SELECTION%20USING%20GENETIC%20ALGORITHMS%20%2824%20pgs%29.pdf text en public http://eprints.utem.edu.my/id/eprint/15883/2/Intership%20supervisor%20selection%20using%20genetic%20algorithms.pdf text en validuser https://plh.utem.edu.my/cgi-bin/koha/opac-detail.pl?biblionumber=96234 mphil masters Universiti Teknikal Malaysia Melaka Faculty of Information and Communication Technology Basiron, Halizah 1. Adamnuthe, A.C. and Bichkar, R.S., 2012. 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Maistry, K., 2014, Task Allocation using GA [Online]. 9. Mitchell, M., 1998. An Introdtrction to Genetic Algorithms, MIT Press Ohara, M. and Tamaki, H., 2012. Integer programming approach for a class of staff scheduling problems - Schedule optimization and parameter estimation. The 6th International Conference on Soft Conzpirting and Intelligent Systems, and The 13th International Sympositrm on Advanced IitelligezcSey stems, pp.877-882. Available at:http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?arnumbe1=6505322, 10. Papadomanolakis, S. and Ailamaki, A,, 2007. An Integer Linear Programming Approach to Database Design. , pp.442449. 11. Qu, R. and He, F., 2009. A hybrid constraint programming approach for nurse rostering problems. Applicatioiis and In17ovatioiis in Intelligent Syste~nsX VI- Proceedings ofAI 2008, the 28th SGAI 12. Intenlatianal Conference on Inliovative Techniques and Applications ofArtijicia1 Intelligence. 2009 pp. 21 1-224. 13. Sabag, N., Trotskovsky, E. and Schecl~nerP, ., 2006. Internship as an Obligatory Requirement for the Degree of B.Sc. in Electronic and Electrical Engineering. 2006 International Colference on 14. Infornzation Technology: Research and Education, pp.94-98. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/mapper.htmlnumber4266302, 15. Sivananda, S., Sathyanarayana, V. and Pati, P.B., 2009. Industiy-Academia Collaboration via Internships. 2009 22nd Coiference on Sofhrare Engineering Education and naining, pp.255-262. Available at: h t t p : / / i e e e x p l o r e . i e e e . o r g / l p d o c s / e p i ~ 8 1 2 7 0 6[A ccessed: 25 November 20141. 16. Sun, J. and Xhafa, F., 201 1. A Genetic Algorithm for Ground Station Scheduling. 2011 International Conference on Complex, Intelligent, and Sofmare Intensive Systems, pp. 138-145. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/wrapper.htm?mumbe5988980 [Accessed: 14 October 20141 17. Swidan, A,Sergey, S. and Dmitry, B., 2013. Using Genetic Algorithms for Solving the Comparison- Based Identification Problem of Multifactor Estimation Model. ,2013(July), pp.349-353. 18. Vairis, A,Loulakakis, K. and Petousis, M., 2013. Enhancing undergraduate courses with internships.2013 24th EAEEIE Anliual Confevence (EAEEIE 2013), pp.28-3 1. Available at: http://ieeexplore.ieee.org/lpdoc~/epic03/wapper.htm?arnumbe~6576496. 19. Wang, Y. and Mo, J., 2013. Emotion feature selection from physiological signals using tabu search.2013 25th Chinese Control and Decision Conference (CCDC), pp.3148-3150. Available at: http://ieeexplore.ieee.org/lpdocs/epic03/mapper.htm?arnumbe~6561487.

Intership supervisor selection using genetic algorithms

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