Automatic Timetabling Using Artificial Immune System

  • Yulan He
  • Siu Cheung Hui
  • Edmund Ming-Kit Lai
Part of the Lecture Notes in Computer Science book series (LNCS, volume 3521)


University timetabling problem is a very common and seemingly simple, but yet very difficult problem to solve in practice. While solution definitely exists (evidenced by the fact that we do hold classes), an automated optimal schedule is very difficult to derive at present. There were successful attempts to address this problem using heuristics search methods. However, until now, university timetabling is still largely done by hand, because a typical university setting requires numerous customized complicated constraints that are difficult to model or automate. In addition, there is a problem of certain constraints being inviolable, while others are merely desirable. This paper intends to address the university timetabling problem that is highly constrained using Artificial Immune System. Empirical study on course timetabling for the School of Computer Engineering (SCE), Nanyang Technological University (NTU), Singapore as well as the benchmark dataset provided by the Metaheuristic Network shows that our proposed approach gives better results than those obtained using the Genetic Algorithm (GA).


Genetic Algorithm Benchmark Problem Soft Constraint Hard Constraint Timetabling Problem 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer-Verlag Berlin Heidelberg 2005

Authors and Affiliations

  • Yulan He
    • 1
  • Siu Cheung Hui
    • 1
  • Edmund Ming-Kit Lai
    • 1
  1. 1.School of Computer EngineeringNanyang Technological UniversitySingapore

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