Genetic Algorithm Calibration for Two Objective Scheduling Parallel Jobs on Hierarchical Grids

  • Victor Hugo Yaurima-Basaldua
  • Andrei Tchernykh
  • Yair Castro-Garcia
  • Victor Manuel Villagomez-Ramos
  • Larisa Burtseva
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7204)


This paper addresses non-preemptive offline scheduling parallel jobs on a Grid. We consider a Grid scheduling model with two stages. At the first stage, jobs are allocated to a suitable Grid site, while at the second stage, local scheduling is independently applied to each site. In this environment, one of the big challenges is to provide a job allocation that allows more efficient use of resources and user satisfaction. In general, the criteria that help achieve these goals are often in conflict. To solve this problem, two-objective genetic algorithm is proposed. We conduct comparative analysis of five crossover and three mutation operators, and determine most influential parameters and operators. To this end multi factorial analysis of variance is applied.


Offline scheduling Grid Genetic Algorithm Crossover Operator Mutation Operator 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • Victor Hugo Yaurima-Basaldua
    • 1
  • Andrei Tchernykh
    • 2
  • Yair Castro-Garcia
    • 3
  • Victor Manuel Villagomez-Ramos
    • 1
  • Larisa Burtseva
    • 3
  1. 1.CESUES Superior Studies CenterSan LuisMexico
  2. 2.CICESE Research CenterEnsenadaMexico
  3. 3.Autonomous University of Baja CaliforniaMexicaliMexico

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