Particle swarm optimization for solving thesis defense timetabling problem

The thesis defense timetabling problem is a fascinating and original NP-hard optimization problem. The problem involves assigning the participants to defense sessions, composing the relevant committees, satisfying the constraints, and optimizing the objectives. This study defines the problem formulation that applies to Universitas Multimedia Nusantara (UMN) and use the particle swarm optimization (PSO) algorithm to solve it. As a demonstration of concept and viability, the proposed method is implemented in a web-based platform using Python and Flask. The implementation is tested and evaluated using real-world instances. The results show that the fastest timetable generation is 0.18 seconds, and the slowest is 21.88 minutes for 25 students and 18 department members, without any violation of the hard constraints. The overall score of the EUCS evaluation for the application is 4.3 out of 6.