MSc Thesis Proposal Announcement of Amanta Sunny:"Metaheuristic Approach to Course Scheduling "

Wednesday, May 5, 2021 - 13:00 to 15:00


The School of Computer Science is pleased to present… 

MSc Thesis Proposal by: Amanta Sunny 

Date: Wednesday, May 5th, 2021 
Time:  1:00pm -3:00pm 
Passcode:   If interested in attending the event, contact the Graduate Secretary at


Nowadays, much research is being carried out to find efficient algorithms for optimal automated university course timetable problems (UCTP). UCTP allocates the university's events like lectures, exams, etc., to the various resources, including instructors, students, lecture time, classrooms, etc.  Class scheduling is one of the biggest challenging problems of educational institutions. In this thesis, the aim is to have a near-optimal solution for a class scheduling problem considering some hard and soft constraints. Hard constraints must be satisfied. Soft constraints need not be satisfied, but there is a penalty for each soft constraint violation. We also have a timing penalty for scheduling each class to a specific schedule. The goal is to allocate classes to their schedule such that the sum of all the penalties is minimum.  
The proposed method follows the metaheuristic approach. We use a modified simulated annealing algorithm by initially changing the cooling function and energy function. We customized the evaluation function by adding a modified penalty, which accelerates the optimization process by making the search more efficient. Further, a focused penalty is added to avoid having a local optimization and lingering over the same value.  We will compare our method with the state-of-art based on the best penalty value vs iteration. 
Keywords: Meta-heuristic, Simulated annealing, Random walk, optimization 

MSc Thesis Committee:  

Internal Reader: Dr Dima Alhadidi             
External Reader: Dr Xiaolei Guo  
Advisor: Dr Jessica Chen 

MSc Thesis Proposal Announcement   Vector Institute artificial intelligence approved topic logo

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