A Greedy and Genetic Fusion Algorithm for Solving Course Timetabling Problem

Abstract

In 1976, S. Even and Cooper proved that Course Timetabling Problem (CTP) is a nondeterministic polynomial time-complete problem which is hard to be solved. Though many intelligent methods have been applied to solve the Course Timetabling Problem in recent years, there is still a lot of room for improvement. This paper proposed a Greedy and Genetic Fusion Algorithm (GGFA) to solve Course Timetabling Problem efficiently, which can obtain the local optimal solution by using Greedy Algorithm and provide a high-quality initial population for Genetic Algorithm. Simulation results prove that Greedy and Genetic Fusion Algorithm proposed in this paper has the stronger optimal ability and faster convergence speed than standard Genetic Algorithm, which could solve the CTP effectively and achieved good results.