Exam scheduling algorithms. (c1999)

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dc.contributor.author Mikati, Ziad
dc.date.accessioned 2011-05-17T07:39:46Z
dc.date.available 2011-05-17T07:39:46Z
dc.date.copyright 1999 en_US
dc.date.issued 2011-05-17
dc.date.submitted 1999-06
dc.identifier.uri http://hdl.handle.net/10725/469
dc.description Includes bibliographical references (p. 92). en_US
dc.description.abstract Scheduling final exams for large numbers of courses and students in liberal arts universities, such as the Lebanese American University (LAU), is an intractable problem. When scheduling is done manually, conflicts and unfairness are inevitable. Conflicts occur when simultaneous exams are scheduled for the same student, and unfairness to a student refers to consecutive exams or more than two exams on the same day. A good exam schedule at LAU would aim for minimizing conflicts and the two unfairness factors based on user assigned weights to these three factors and subject to some constraints. This report presents the implementation of a Final Exam Scheduling Package (FESP) at L.A.U. FESP distributes the final exams among the exam sessions and assigns exams to classrooms. It aims for minimizing student conflicts such as students with simultaneous exams, consecutive exams and more than two exams per day. It also allows sharing classrooms among exams. This work also includes an improved natural optimization algorithm for exam scheduling, the Genetic Algorithm (GA). The problem is first formulated as a modified weighted-graph-coloring problem. Then the genetic algorithm is adapted for solving the exam scheduling problem taking into account the specific objectives and constraints of LAU. Then, we compare the results of the two algorithms and with a manual procedure. The experimental results obtained on real-life data show that FESP yields a substantial decrease in the number of exam conflicts in comparison with those obtained by the GA and the manually prepared exam schedule. en_US
dc.language.iso en en_US
dc.subject Genetic algorithms en_US
dc.title Exam scheduling algorithms. (c1999) en_US
dc.type Thesis en_US
dc.term.submitted Spring en_US
dc.author.degree MS in Computer Science en_US
dc.author.school Arts and Sciences en_US
dc.author.commembers Dr. May Abboud
dc.author.commembers Dr. Rarnzi Haraty
dc.author.woa RA en_US
dc.description.physdesc 1 bound copy: vii, 92 leaves; ill., tables; 30 cm. available at RNL. en_US
dc.author.division Computer Science en_US
dc.author.advisor Dr. Nash'at Mansour
dc.keywords Exam scheduling en_US
dc.keywords FESP en_US
dc.keywords Genetic algorithms en_US
dc.identifier.doi https://doi.org/10.26756/th.1999.5 en_US
dc.publisher.institution Lebanese American University en_US

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