Majumdar, Mahbubul AlamHasan, ShafqatDofadar, Dibyo FabianKhan, Riyo HayatTaj, Towshik Anam2024-11-172024-11-17©20212021-01ID 20241046ID 17101407ID 16201062ID 20241045http://hdl.handle.net/10361/24792Catalogued from PDF version of thesis.Includes bibliographical references (pages 48-51).This thesis is submitted in partial fulfillment of the requirements for the degree of Bachelor of Science in Computer Science, 2021.This paper discusses about various types of constraints, regulations, difficulties and solutions to overcome the challenges regarding university departmental course allocation problem. A CSP solver algorithm, Genetic Algorithm, Simulated Annealing and a hybrid of Genetic Algorithm and Simulated Annealing has been used separately to generate the best course assignment and also to compare the results generated by these four algorithms. The Department of Computer Science and Engineering of BRAC University has been used as a case study to discover the scope of automation in this research. After analyzing the information gathered from the department itself, some constraints were formulated. These constraints manage to cover all the aspects needed to be kept in mind while preparing a class schedule for a faculty member without any clashes. The goal is to generate optimized solution(s) which will fulfill those constraints. At this point, the main focus is on the perspective of the faculty members but in the near future, there will be enough opportunities for expansions, like focusing on the lab change procedure of the students, assignment of student tutors and many more.52 pagesenBrac University theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission.Course allocationCSP solverComputer algorithmsSimulated annealingHybrid algorithmSimulated annealing (Mathematics).Genetic algorithms.Artificial intelligenceConstraint programming (Computer science).Thesis