Abstract
Scheduling is one of the core steps to efficiently exploit the capabilities of heterogeneous distributed computing systems and it is also an appealing NPcomplete problem. There is a number of heuristic and meta-heuristic algorithms that were tailored to deal with scheduling of independent jobs. In this paper we investigate the efficiency of differential evolution for the scheduling problem and compare it with existing approaches. The analysis shows that the differential evolution is a promising method that can compete with well-established scheduling algorithms.
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Krömer, P., Snášel, V., Platoš, J., Abraham, A., Ezakian, H. (2010). Evolving Schedules of Independent Tasks by Differential Evolution. In: Caballé, S., Xhafa, F., Abraham, A. (eds) Intelligent Networking, Collaborative Systems and Applications. Studies in Computational Intelligence, vol 329. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-16793-5_4
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DOI: https://doi.org/10.1007/978-3-642-16793-5_4
Publisher Name: Springer, Berlin, Heidelberg
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