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A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids

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Hybrid Evolutionary Algorithms

Part of the book series: Studies in Computational Intelligence ((SCI,volume 75))

In this chapter we present a hybrid evolutionary metaheuristic based on memetic algorithms (MAs) and several local search algorithms. The memetic algorithm is used as the principal heuristic that guides the search and can use any of the 16 local search algorithms during the search process. The local search algorithms used in combination with the MA are obtained by fixing either the type of the neighborhood or the type of the move; they include swap/move based search, Hill Climbing, Variable Neighborhood Search, and Tabu Search. The proposed hybrid metaheuristic is implemented in C++ using a generic approach based on a skeleton for MAs. The implementation has been extensively tested in order to identify a set of appropriate values for the MA and local search parameters. We have comparatively studied the combination of MA with different local search algorithms in order to identify the best hybridization. Results are compared with the best known results for the problem in the evolutionary computing literature, namely the benchmark of Braun et al. (2001), which is known to be the most difficult benchmark for static instances of the problem. Our experimental study shows that the MA+ TS hybridization outperforms the combinations of MA with other local search algorithms considered in this work and also improves the results of Braun et al. for all considered instances. We also discuss some issues related to the fine tuning and experimenting of metaheuristics in a dynamic environment.

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Authors
  1. F. Xhafa
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Editor information

Editors and Affiliations

  1. Norwegian University of Science and Technology, O.S. Bragstads plass 2E, N-7491, Trondheim, Norway

    Ajith Abraham

  2. Babes-Bolyai University, Kogalniceanu 1, 400084, Cluj-Napoca, Romania

    Crina Grosan

  3. Osaka Prefecture University, 1-1 Gakuen-cho, 599-8531, Naka-ku, Sakai Osaka, Japan

    Hisao Ishibuchi

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Xhafa, F. (2007). A Hybrid Evolutionary Heuristic for Job Scheduling on Computational Grids. In: Abraham, A., Grosan, C., Ishibuchi, H. (eds) Hybrid Evolutionary Algorithms. Studies in Computational Intelligence, vol 75. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-73297-6_11

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  • DOI: https://doi.org/10.1007/978-3-540-73297-6_11

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-73296-9

  • Online ISBN: 978-3-540-73297-6

  • eBook Packages: EngineeringEngineering (R0)

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