Matching based very large-scale neighborhoods for parallel machine scheduling


Brueggemann, Tobias and Hurink, Johann L. (2011) Matching based very large-scale neighborhoods for parallel machine scheduling. Journal of Heuristics, 17 (6). pp. 637-658. ISSN 1381-1231

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Abstract:In this paper we study very large-scale neighborhoods for the minimum total weighted completion time problem on parallel machines, which is known to be strongly NP-hard. We develop two different ideas leading to very large-scale neighborhoods in which the best improving neighbor can be determined by calculating a weighted matching. The first neighborhood is introduced in a general fashion using combined operations of a basic neighborhood. Several examples for basic neighborhoods are given. The second approach is based on a partitioning of the job sets on the machines and a reassignment of them. In a computational study we evaluate the possibilities and the limitations of the presented very large-scale neighborhoods.
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Copyright:© 2011 The Author(s)
Electrical Engineering, Mathematics and Computer Science (EEMCS)
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