Sawaphat Jaengchuea. A hybrid multi-objective evolutionary algorithm with a local search approach for solving the post enrolment based course timetabling problem. Master's Degree(Applied Mathematics). King Mongkut's University of Technology North Bangkok. Central Library. : King Mongkut's University of Technology North Bangkok, 2014.
A hybrid multi-objective evolutionary algorithm with a local search approach for solving the post enrolment based course timetabling problem
Abstract:
The post enrolment based course timetabling problem (PECTP) is one type of university course timetabling problem, which a set of events has to be assigned into time slots and suitable rooms according to students enrolment data. The PECTP is a real world problem and it commonly occurs in every educational institution in every semester. This problem is classified as a combinatorial optimization problem and it is very hard to solve the problem efficiently because solving the problem is to find an optimal timetable which it must satisfy all hard constraints and should satisfy soft constraints as much as possible. As a result, this problem is technically complicated and highly time-consuming and it is known to be in the NP-complete class. In addition, the nature of this problem also naturally leads to multiple objective functions as there is usually more than one objective that needs to be simultaneously optimized. In this research we develop a multi-objective evolutionary algorithm hybridized with local search approaches for solving the PECTP. The algorithm takes advantage of the exploitation ability from local search technique and tabu search heuristic to improve the results obtained in the exploration phase of the evolutionary algorithm. The algorithm was tested on a set of problem instances from Metaheuristic Network, a standard benchmark for evaluating the proposed hybrid algorithm. The experimental results of proposed hybrid approach comparing with other methods from the literature have shown that the proposed hybrid approach is able to find promising solutions for solving the PECTP