A New Genetic Algorithm for University Course Timetabling Problem

This paper considers a Genetic Algorithm (GA) for University Course Timetabling Problem (UCTP). UCTP is one of the important and time onsuming issues that each university is involved with it at the beginning of each. This problem is in class of NP-hard problem. The main components of the genetic operators in a GA will be tested and the best combination of the genetic operators will be adopted to construct a Pure Genetic Algorithm (PGA). The PGA will then hybridize with four new local optimization techniques, which will make up the Hybrid Genetic Algorithm (HGA) to improve the solutions found. In order to test the performance of proposed HGA, experiments were carried out on a set of benchmark UCTP instances. The experimental results indicate that the proposed HGA is able to produce promising results for the UCTP.

Keywords:

university course timetabling problem , genetic algorithm , local optimization techniques