A Web-based Course Scheduler Integrated with Effective Heuristics and Genetic Algorithm Technique

J.N.K. Liu, (PRC), R. Hung (Australia), and R.S.T. Lee (PRC)


Genetic Algorithm, course scheduler, heuristics strategies, Web-based system.


To enhance the timetabling process, a Web-based course scheduler is developed in the present paper. It incorporates with effective heuristics and genetic algorithm (GA) technique to solve problems that satisfy the schedule constraints in sets of limited resources. Different strategies are applied to estimate the degree of constraint of lesson, namely random/natural ordering, longest-first, and approximately-most-constrained-first strategies on one hand, and strategies to assign lesson to a timeslot in the timetable, namely first-around, random, and evenly distributed strategies on the other. For the GA implementation, we apply scheduling cost to determine which class-scheduling chromosomes are reserved instead of using the fitness value. Promising results with better generation can be obtained. The proposed techniques therefore are complementary each other.

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