A Hybrid Shuffled Frog-Leaping Algorithm for the University Examination Timetabling Problem

  • Nuno Leite
  • Fernando Melício
  • Agostinho C. Rosa
Chapter
Part of the Studies in Computational Intelligence book series (SCI, volume 613)

Abstract

The problem of examination timetabling is studied in this work. We propose a hybrid solution heuristic based on the Shuffled Frog-Leaping Algorithm (SFLA) for minimising the conflicts in the students’s exams. The hybrid algorithm, named Hybrid SFLA (HSFLA), improves a population of frogs (solutions) by iteratively optimising each memeplex, and then shuffling the memeplexes in order to distribute the best performing frogs by the memeplexes. In each iteration the frogs are improved based on three operators: crossover and mutation operators, and a local search operator based on the Simulated Annealing metaheuristic. For the mutation and local search, we use two well known neighbourhood structures. The performance of the proposed method is evaluated on the 13 instances of the Toronto datasets from the literature. Computational results show that the HSFLA is competitive with state-of-the-art methods, obtaining the best results on average in seven of the 13 instances.

Keywords

Examination timetabling Memetic algorithm Shuffled Frog-Leaping Algorithm Simulated annealing Toronto benchmarks 

Notes

Acknowledgments

Nuno Leite wishes to thank FCT, Ministério da Ciência e Tecnologia, his Research Fellowship SFRH/PROTEC/67953/2010. This work was supported by the FCT Project PEst-OE/EEI/LA0009/2013.

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Copyright information

© Springer International Publishing Switzerland 2016

Authors and Affiliations

  • Nuno Leite
    • 1
    • 2
  • Fernando Melício
    • 1
    • 2
  • Agostinho C. Rosa
    • 2
    • 3
  1. 1.Instituto Superior de Engenharia de Lisboa/IPLLisboaPortugal
  2. 2.LaSEEB-System and Robotics InstituteLisboaPortugal
  3. 3.Department of Bioengineering/ISTUniversidade de LisboaLisboaPortugal

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