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Course Timetabling

AUTOMATED COURSE AND EXAMINATION TIMETABLING Dr. S. Kanmani Professor and Head Department of Information Technology Pondicherry Engineering College Puducherry --605 014 kanmani@pec.edu. Course Timetabling.

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Course Timetabling

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  1. AUTOMATED COURSE AND EXAMINATION TIMETABLING Dr. S. KanmaniProfessor and Head Department of Information Technology Pondicherry Engineering College Puducherry --605 014 kanmani@pec.edu

  2. Course Timetabling • Course Timetabling is an event of scheduling of lectures for subjects in each course in the specified rooms and timeslots • The feasibility of Scheduling depends on the flexibility and effectiveness of assigning subjects for courses and teachers in a week • The resultant timetable must fulfill the constraints for feasibility and optimality

  3. Course Timetabling - constraints • Student conflict • Teacher conflict • Room conflict • Other soft constraints

  4. Examination Scheduling • Examination Timetabling is scheduling of Exam timings for various subjects of different courses in the specified rooms and in the allotted duration • The resultant timetable must fulfill the constraints for feasibility • Though a number of feasible solutions are possible the best optimal solution need to be identified

  5. Examination Scheduling - Constraints • Rooms • Resources • Examiners • Students

  6. Objectives • To design and implement the Course and Examination timetabling for the courses offered in 6 different disciplines • To improve the flexibility in assigning and changing the allotment based on the needs of teachers and students • By this automated scheduling, class hours will be evenly distributed without any bias and examinations could be scheduled without any violation • To minimize the Preparation time of the human resources • To implement error free scheduling • To have central monitoring, easy retrieval and uniform distribution of class hours for students / faculty members, laboratories and classrooms.

  7. Automated Timetabling Features • More than one Institution • Flexibility to change • Getting the best Always • Not trial and error • Minimum time • Effective utilization of resources • Easy monitoring / control • Even Distribution

  8. International / National Development • University of Nottingham, UK • www .nottingham. ac .uk /timetable • Napier University, Edinberg • www.napier.ac.uk • University of Technology Malaysia(UiTM) • www.uitm.edu • University Kebangsaan Malaysia • http://www.ftsm.ukm.my/ • IIT Kanpur , India • www.iitk.ac.in

  9. Courses to be considered

  10. Recurring Budget

  11. Non-Recurring Budget

  12. Implementation Phases Phase I : Study of the assumptions, conditions and constraints exist in the manual system in each of the institutions and generalization Phase II :Development of Data bases for common details (subjects, credits, etc) and specific details (faculty name, lab name, etc,..) Phase III :Applying suitable techniques to find the initial solution Phase IV :Experimenting the various optimization techniques Phase V :Optimization of the solution and identifying the best method

  13. Work Done • Class Timetabling for one UG Science course has been attempted with Artificial Intelligence • Course Timetabling is being explored now.

  14. THANK YOU

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