December 2011, Volume 17, Issue 6, pp 637658,
Open Access
This content is freely available online to anyone, anywhere at any time.
Date:
11 Nov 2010
Matching based very largescale neighborhoods for parallel machine scheduling
 Tobias Brueggemann,
 Johann L. Hurink
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Abstract
In this paper we study very largescale neighborhoods for the minimum total weighted completion time problem on parallel machines, which is known to be strongly \(\mathcal{NP}\) hard. We develop two different ideas leading to very largescale 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 largescale neighborhoods.
T. Brueggemann was supported by the Netherlands Organization for Scientific Research (NWO) grant 613.000.225 (Local Search with Exponential Neighborhoods).
J.L. Hurink was supported by BSIK grant 03018 (BRICKS: Basic Research in Informatics for Creating the Knowledge Society).
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 Title
 Matching based very largescale neighborhoods for parallel machine scheduling
 Open Access
 Available under Open Access This content is freely available online to anyone, anywhere at any time.
 Journal

Journal of Heuristics
Volume 17, Issue 6 , pp 637658
 Cover Date
 20111201
 DOI
 10.1007/s1073201091498
 Print ISSN
 13811231
 Online ISSN
 15729397
 Publisher
 Springer US
 Additional Links
 Topics
 Keywords

 Scheduling
 Parallel machines
 Total weighted completion time
 Very largescale neighborhoods
 Local search
 Industry Sectors
 Authors

 Tobias Brueggemann ^{(1)}
 Johann L. Hurink ^{(1)}
 Author Affiliations

 1. Department of Applied Mathematics, University of Twente, P.O. Box 217, 7500 AE, Enschede, The Netherlands