Applied Intelligence

, Volume 42, Issue 4, pp 679–693 | Cite as

Hybridising heuristics within an estimation distribution algorithm for examination timetabling

  • Rong QuEmail author
  • Nam Pham
  • Ruibin Bai
  • Graham Kendall


This paper presents a hybrid hyper-heuristic approach based on estimation distribution algorithms. The main motivation is to raise the level of generality for search methodologies. The objective of the hyper-heuristic is to produce solutions of acceptable quality for a number of optimisation problems. In this work, we demonstrate the generality through experimental results for different variants of exam timetabling problems. The hyper-heuristic represents an automated constructive method that searches for heuristic choices from a given set of low-level heuristics based only on non-domain-specific knowledge. The high-level search methodology is based on a simple estimation distribution algorithm. It is capable of guiding the search to select appropriate heuristics in different problem solving situations. The probability distribution of low-level heuristics at different stages of solution construction can be used to measure their effectiveness and possibly help to facilitate more intelligent hyper-heuristic search methods.


Estimation distribution algorithm Hyper-heuristic Exam timetabling Graph colouring 


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Copyright information

© Springer Science+Business Media New York 2014

Authors and Affiliations

  • Rong Qu
    • 1
    Email author
  • Nam Pham
    • 1
  • Ruibin Bai
    • 2
  • Graham Kendall
    • 1
    • 3
  1. 1.Automated Scheduling, Optimisation and PlanningSchool of Computer Science University of NottinghamNottinghamUK
  2. 2.School of Computer ScienceUniversity of Nottingham Ningbo, ChinaNingboChina
  3. 3.University of Nottingham Malaysia CampusNottinghamMalaysia

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