A GA(TS) Hybrid Algorithm for Scheduling in Computational Grids

Authors:
Fatos Xhafa;Juan A. Gonzalez;Keshav P. Dahal;Ajith Abraham
Affiliations:
Department of Languages and Informatics Systems, Technical University of Catalonia, Barcelona, Spain;Department of Languages and Informatics Systems, Technical University of Catalonia, Barcelona, Spain;School of Informatics, University of Bradford, UK;Center of Excellence for Quantifiable Quality of Service, Norwegian University of Science and Technology, Norway
Venue:
HAIS '09 Proceedings of the 4th International Conference on Hybrid Artificial Intelligence Systems
Year:
2009

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Abstract

The hybridization of heuristics methods aims at exploring the synergies among stand alone heuristics in order to achieve better results for the optimization problem under study. In this paper we present a hybridization of Genetic Algorithms (GAs) and Tabu Search (TS) for scheduling in computational grids. The purpose in this hybridization is to benefit the exploration of the solution space by a population of individuals with the exploitation of solutions through a smart search of the TS. Our GA(TS) hybrid algorithm runs the GA as the main algorithm and calls TS procedure to improve individuals of the population. We evaluated the proposed hybrid algorithm using different Grid scenarios generated by a Grid simulator. The computational results showed that the hybrid algorithm outperforms both the GA and TS for the makespan value but cannot outperform them for the flowtime of the scheduling.