Simulated annealing and genetic algorithms for exam scheduling. (c1997)

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dc.contributor.author Tarhini, Abbas A.
dc.date.accessioned 2011-04-08T12:30:37Z
dc.date.available 2011-04-08T12:30:37Z
dc.date.copyright 1997 en_US
dc.date.issued 2011-04-08
dc.date.submitted 1997-06
dc.identifier.uri http://hdl.handle.net/10725/334
dc.description Includes bibliographical references. en_US
dc.description.abstract Scheduling final exams for large numbers of courses and students in Liberal Arts Universities is an intractable problem. If scheduling is done manually by the University Registrar's Office, a huge number of complaints will be raised by students about the unfairness of the schedule. Unfairness refers to conflicting simultaneous exams, consecutive exams, or giving more than two exams on the same day. In this work, we propose a simulated annealing algorithm and a classical genetic algorithm for exam scheduling. The experimental results, using realistic data, show that simulated annealing and genetic algorithms give better exam schedules than both manual scheduling and another heuristic method, in a reasonable time. Further, these algorithms are flexible and allow giving multi-section exams at the same time and pre-selecting certain exams. en_US
dc.language.iso en en_US
dc.subject Simulated annealing (Mathematics) en_US
dc.subject Genetic algorithms en_US
dc.subject Examinations en_US
dc.title Simulated annealing and genetic algorithms for exam scheduling. (c1997) en_US
dc.type Thesis en_US
dc.term.submitted Spring en_US
dc.author.school Arts and Sciences en_US
dc.author.commembers Ramzi Haraty en_US
dc.author.commembers Walid Keirouz en_US
dc.author.woa RA en_US
dc.author.department MS in Computer Science en_US
dc.description.physdesc 1 bound copy: 1 v. (various pagings); ill.; 30 cm. available at RNL. en_US
dc.author.division Computer Science en_US
dc.author.advisor Nashat Mansour en_US
dc.identifier.doi https://doi.org/10.26756/th.1997.14

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