Enhancing the genetic-based scheduling in computational grids by a structured hierarchical population ✩ Joanna Kolodziej a,∗ , Fatos Xhafa b,1 a University of Bielsko-Biala; Department of Mathematics and Computer Science; ul. Willowa 2, 43-309 Bielsko-Biala, Poland b Department of Computer Science and Information Systems; Birkbeck, University of London; Malet Street, Bloomsbury, London WC1E 7HX, UK. Abstract Independent Job Scheduling is one of the most useful versions of scheduling in Grid sys- tems. It aims at computing efficient and optimal mapping of jobs and/or applications submitted by independent users to the Grid resources. Besides traditional restrictions, mappings of jobs to resources should be computed under high degree of heterogeneity of resources, the large scale and the dynamics of the system. In view of the challenging nature of the problem, heuristic and meta- heuristic approaches are the most feasible candidate methods due to their ability to deliver high quality solutions in reasonable computing time. One class of meta-heuristics, less explored for the problem, is that of Hierarchic Genetic Strategy (HGS), a variant of Genetic Algorithms (GAs) that distinguishes for its capability of concurrent search of the solution space. In this work we present an implementation of HGS for Independent Job Scheduling in dynamic Grid environments. We consider the bi-objective version of the problem in which makespan and flowtime are simultane- ously optimized. Building on our previous work, we improve the HGS scheduling strategy for the problem, by enhancing its main branching operation. The resulting HGS-based scheduler is evaluated under the heterogeneity, the large scale and dynamics conditions using a Grid simula- tor. The experimental study showed that the HGS implementation outperforms existing GA-based schedulers proposed in the literature. Keywords: Scheduling, Computational Grid, Genetic Algorithms, Hierarchic Genetic Strategies, ETC Matrix Model, Grid Simulation. ✩ A preliminary version of this paper appeared at 23rd European Conference on Modelling and Simulation (ECMS 2009), Madrid, Spain ∗ Corresponding author Email addresses: jkolodziej@ath.bielsko.pl (Joanna Kolodziej ), fatos@dcs.bbk.ac.uk; fatos@lsi.upc.edu (Fatos Xhafa ) 1 On leave from Technical University of Catalonia, Spain. © 2011 Elsevier. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/