Abstract
The curriculum-based university course timetabling which has been established as non-deterministic polynomial problem involves the allocation of timeslots and rooms for a set of courses depend on the hard or soft constraints that are listed by the university. To solve the problem, firstly a set of hard constraints were fulfilled in order to obtain a feasible solution. Secondly, the soft constraints were fulfilled as much as possible. In this paper we focused to satisfy the soft constraints using a hybridization of harmony search with a great deluge. Harmony search comprised of two main operators such as memory consideration and random consideration operator. The hybridization consisted three setups based on the application of great deluge on the operators of the harmony search. The great deluge was applied either on the memory consideration operator, or random consideration operator or both operators together. In addition, several harmony memory consideration rates were applied on those setups. The algorithms of all setups were tested on curriculum-based datasets taken from the International Timetabling Competition, ITC2007. The results demonstrated that our approach was able to produce comparable solutions (with lower penalties on several data instances) when compared to other techniques from the literature.
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Wahid, J., Hussin, N.M. (2015). Solving Curriculum Based Course Timetabling by Hybridizing Local Search Based Method within Harmony Search Algorithm. In: Berry, M., Mohamed, A., Yap, B. (eds) Soft Computing in Data Science. SCDS 2015. Communications in Computer and Information Science, vol 545. Springer, Singapore. https://doi.org/10.1007/978-981-287-936-3_14
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DOI: https://doi.org/10.1007/978-981-287-936-3_14
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