Abstract
Scheduling n independent jobs on m unrelated parallel machines without preemption belongs to the most difficult scheduling problems. Here, processing job i on machine j takes time p ij , and the total time used by a machine is the sum of the processing times for the jobs assigned to it. The objective is to minimize makespan. In this paper we present an experimental study on the Unsplittable-Truemper algorithm. This purely combinatorial approach computes 2-approximate solutions in the best worst-case running time known so far. The goal of our simulations was to prove its efficiency in practice. We compare our technique with algorithms and heuristics used in practice, especially with those based on the two-step approach. The experiments show that for large and difficult instances the Unsplittable-Truemper algorithm has a clear advantage over methods based on linear programming. Moreover, it requires much less operational memory, and thus is more effective and easier to handle.
This work has been partially supported by the DFG-Sonderforschungsbereich 376 Massive Parallelität: Algorithmen, Entwurfsmethoden, Anwendungen, by the European Union within the 6th Framework Program under contract 001907 (DELIS) and by the DFG Research Training Group GK-693 of the Paderborn Institute for Scientific Computation (PaSCo).
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Monien, B., Woclaw, A. (2006). Scheduling Unrelated Parallel Machines Computational Results. In: Àlvarez, C., Serna, M. (eds) Experimental Algorithms. WEA 2006. Lecture Notes in Computer Science, vol 4007. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11764298_18
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DOI: https://doi.org/10.1007/11764298_18
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