Hierarchic vs. Single–Population and Hybrid Metaheuristic Grid Schedulers: A Comparative Empirical Study

  • Joanna Kołodziej
Part of the Studies in Computational Intelligence book series (SCI, volume 419)


This chapter presents the results of comprehensive empirical evaluation of hierarchical, hybrid, single- and multi-population genetic metaheuristics in static and dynamic versions of the scheduling problem in grid. All metaheuristics have been integrated with the Sim-G-Batch grid simulator. The results of the analysis show the high effectiveness of HGS-Sched in exploration of the bi-objective dynamic optimization landscapes in highly-parametrized grids.


Genetic Algorithm Tabu Search Tabu Search Algorithm Grid Simulator Tuning Process 
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Copyright information

© Springer-Verlag GmbH Berlin Heidelberg 2012

Authors and Affiliations

  1. 1.Institute of Computer Science Cracow University of TechnologyCracowPoland

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