A new hybrid particle swarm optimization algorithm for real-world university examination timetabling problem

Timetabling is a discrete and combinatorial optimization problem. It is usually handled with heuristic and/or artificial intelligent approaches. Examination timetabling problem is part of Timetabling problem that consists of allocating a set of exams (courses) in a finite period of time while satisfying a set of constraints of various types. Examination timetabling problem have still been studying due to their wide applications. Particle Swarm Optimization (PSO) technique is a well-known intelligent method that has been successfully applied to many hard combinatorial optimization problems but not widely used in this field of problem. In this paper, we propose a new hybrid approach based on PSO. The proposed algorithm has considerable results and usually a good stability.