Multi Population Hybrid Genetic Algorithms for University Course Timetabling

Meysam Shahvali Kohshori () and Mehrnaz Shirani Liri ()
Additional contact information
Meysam Shahvali Kohshori: Department of Computer Engineering, Izeh Brach, Islamic Azad University, Izeh, Iran
Mehrnaz Shirani Liri: Department of Computer Engineering, Izeh Brach, Islamic Azad University, Izeh, Iran

Economics and Applied Informatics, 2012, issue 2, 5-16

Abstract: University course timetabling is one of the important and time consuming issues that each University is involved with at the beginning of each university year. This problem is in class of NP-hard problem and is very difficult to solve by classic algorithms. Therefore optimization techniques are used to solve them and produce optimal or almost optimal feasible solutions instead of exact solutions. Genetic algorithms, because of their multidirectional search property, are considered as an efficient approach for solving this type of problems. In this paper three new hybrid genetic algorithms for solving the university course timetabling problem (UCTP) are proposed: FGARI, FGASA and FGATS. In the proposed algorithms, fuzzy logic is used to measure violation of soft constraints in fitness function to deal with inherent uncertainty and vagueness involved in real life data. Also, randomized iterative local search, simulated annealing and tabu search are applied, respectively, to improve exploitive search ability and prevent genetic algorithm to be trapped in local optimum. The experimental results indicate that the proposed algorithms are able to produce promising results for the UCTP

Keywords: University course timetabling problem(UCTP); Genetic algorithm; Multi population; Fuzzy logic; Local search; Heurestics (search for similar items in EconPapers)
JEL-codes: I20 I21 (search for similar items in EconPapers)
Date: 2012
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (1)

Downloads: (external link)
http://www.ann.ugal.ro/eco/Doc2012.2/Meysam%20Shah ... 20Shirani%20LIRI.pdf (application/pdf)

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:ddj:fseeai:y:2012:i:2:p:5-16

Access Statistics for this article

More articles in Economics and Applied Informatics from "Dunarea de Jos" University of Galati, Faculty of Economics and Business Administration Contact information at EDIRC.
Bibliographic data for series maintained by Gianina Mihai ().