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TAVLAMA BENZETİMİ ALGORİTMASINI KULLANARAK FAKÜLTE DERSLERİNİN ÇİZELGELENMESİ

TIMETABLING OF FACULTY LECTURES USING SIMULATED ANNEALING ALGORITHM

Journal Name:

  • İstanbul Ticaret Üniversitesi Fen Bilimleri Dergisi

Publication Year:

  • 2007

Key Words:

Keywords (Original Language):

Author NameUniversity of AuthorFaculty of Author
Abstract (2. Language): 
In this study, a faculty-course timetabling problem is solved by using a Simulated Annealing based algorithm. In this sort of problems, both the objectives and the constraints are usually highly institution-specific. Thus, there is not a single commonly usedtool to solve this planning problem. Since the problems are institution-specific, the results of this study have not beencompared to those of the studies which are published already. Comparing with the many of the studies, the most important difference of this study is to take the lecturer seniority into consideration. This study separates the problem into two main components in the solution progress. While the first one is dealing with searching of the lectures which can be located into the same time interval, the second one is dealing with assigning the lectures to the most suitable place in the timetable. That algorithm is experimented with 2006-2007 academic year first term data of Faculty of Business Administration at Istanbul University. The results of proposed algorithm is compared to those of genetic algorithms and tabu search. Thus, the genetic algorithms approach can not even find a feasible solution. And the tabu search approach finds worse solutions than the proposed algorithm.
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Abstract (Original Language): 
Bu çalışmada fakülte derslerinin çizelgelenmesi problemi Tavlama Benzetimi temelli bir algoritma ile çözülmüştür. Bu tür problemlerde hem amaçlar hem de kısıtlar genellikle kuruma özgüdür. Bu nedenle böyle bir planlama problemini çözecek ortak bir araç bulunmamaktadır. Problemlerin kuruma özgü olmasınedeniyle çalışmanın sonuçlarıliteratürdeki bir çalışmanın sonuçlarıyla karşılaştırılamamıştır. Bu çalışmanın literatürde yer alan pek çok çalışmadan en önemli farklarından birisi öğretim üyesi kıdemlerinin dikkate alınmışolmasıdır. Çözüm sürecinde problem iki ana parçaya ayrılmıştır. Bunlardan birincisi aynızaman dilimine yerleştirilebilecek dersleri aramakla ilgilenirken, ikincisi derslerin zaman çizelgesinde en uygun yerlere yerleştirilmesiyle ilgilenmektedir. Algoritma İstanbul Üniversitesi İşletme Fakültesi’ nin 2006-2007 Akademik takvimi birinci yarıyıl verileriyle denenmiştir. Önerilen algoritmanın sonuçlarıile genetik algoritmalar ve tabu arama algoritmalarının sonuçlarıkıyaslanmıştır. Buna göre, genetik algoritmalar yaklaşımıuygun çözüm dahi bulamamaktadır. Tabu arama yaklaşımıise daha başarısız çözümler bulmaktadır.
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  • 12
1-20
  • English

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