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Genetic Algorithm and Tabu Search Memory with Course Sandwiching (GATS_CS) for University Examination Timetabling


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Abstract

Abstract: Educational Institutions use timetables to maximize and optimize scarce resources like time and space when scheduling classes, lectures, examinations or events. This makes University timetable scheduling a complicated constraint problem. This study aims to develop an examination timetable system for a University to solve the problems associated with the present manual technique such as un-allocation of courses, course clashes, course duplication, multiple examinations per hall, elongated and laborious reviews, etc. The hybrid of meta-heuristics procedures: Genetic Algorithm (GA) and Tabu Search (TS) memory was employed along with course sandwiching (GATS_CS) to develop an improved automatic University examination timetable solution. For implementation, a case study of a public University in Nigeria was used. The concepts of Genetic Algorithm: Selection, Evaluation were implemented while memory properties of TS and course sandwiching was used to replaced genetic operators of Crossover and Mutation. Course allocation and hall scheduling was optimized based on defined constraints for the case study University while GAT_CS was implemented in Java. Result obtained showed that GAT_CS allocated 96.07% and 99.02% of the total courses to exam halls, un-allocated 3.93% and 0.98% for first and second semesters, respectively. Also, in several instances it automatically sandwiched (scheduled) multiple examinations into a single hall without exceeding the hall's exam sitting capacity. GAT_CS also outperformed Particle Swarm Optimization and Local Search (PSO_LS) and Generic Algorithm (GA) based timetable implementations when benchmarked with the same timetable dataset. The system could be improved to reduce clashes, duplication, multiple examinations and accommodate more system defined constraints for future directions.


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Total Pages: 19

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Published

Online Article

JOURNAL INFORMATION


ISSN PRINT: 1079-8587
ISSN ONLINE: 2326-005X
DOI PREFIX: 10.31209
10.1080/10798587 with T&F
IMPACT FACTOR: 0.652 (2017/2018)
Journal: 1995-Present




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