Abstract
In many industrial and computing applications, proper scheduling of tasks can determine the overall efficiency of the system. The algorithm, presented in this paper, tackles the scheduling problem in a multi-layer multiprocessor environment, which exists in many computing and industrial applications. Based on the scheduling terminology, the problem can be defined as multiprocessor task scheduling in hybrid flow-shops. This paper presents a particle swarm optimization algorithm for the solution and reports its performance. The results are compared with other well known meta-heuristic techniques proposed for the solution of the same problem. Our results show that particle swarm optimization has merits in solving multiprocessor task scheduling in a hybrid flow-shop environment.
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Ercan, M.F., Fung, YF. (2007). Performance of Particle Swarm Optimization in Scheduling Hybrid Flow-Shops with Multiprocessor Tasks. In: Gervasi, O., Gavrilova, M.L. (eds) Computational Science and Its Applications – ICCSA 2007. ICCSA 2007. Lecture Notes in Computer Science, vol 4707. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74484-9_27
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DOI: https://doi.org/10.1007/978-3-540-74484-9_27
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