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European Conference on Evolutionary Computation in Combinatorial Optimization

EvoCOP 2017: Evolutionary Computation in Combinatorial Optimization pp 1–17Cite as

A Computational Study of Neighborhood Operators for Job-Shop Scheduling Problems with Regular Objectives

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 10197))

Abstract

Job-shop scheduling problems have received a considerable attention in the literature. While the most tackled objective in this area is makespan, job-shop scheduling problems with other objectives such as the minimization of the weighted or unweighted tardiness, the number of late jobs, or the sum of the jobs’ completion times have been considered. However, the problems under the latter objectives have been generally less studied than makespan. In this paper, we study job-shop scheduling under various objectives. In particular, we examine the impact various neighborhood operators have on the performance of iterative improvement algorithms, the composition of variable neighborhood descent algorithms, and the performance of metaheuristics such as iterated local search in dependence of the type of local search algorithm used.

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Acknowledgments

This research and its results have received funding from the COMEX project (P7/36) within the Interuniversity Attraction Poles Programme of the Belgian Science Policy Office. Thomas Stützle acknowledges support from the Belgian F.R.S.-FNRS, of which he is a Senior Research Associate.

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Authors and Affiliations

  1. IRIDIA, Université libre de Bruxelles (ULB), Brussels, Belgium

    Hayfa Hammami & Thomas Stützle

Authors
  1. Hayfa Hammami
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  2. Thomas Stützle
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Correspondence to Hayfa Hammami .

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Editors and Affiliations

  1. Austrian Institute of Technology, Vienna, Austria

    Bin Hu

  2. University of Manchester, Manchester, United Kingdom

    Manuel López-Ibáñez

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Hammami, H., Stützle, T. (2017). A Computational Study of Neighborhood Operators for Job-Shop Scheduling Problems with Regular Objectives. In: Hu, B., López-Ibáñez, M. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2017. Lecture Notes in Computer Science(), vol 10197. Springer, Cham. https://doi.org/10.1007/978-3-319-55453-2_1

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  • DOI: https://doi.org/10.1007/978-3-319-55453-2_1

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-55452-5

  • Online ISBN: 978-3-319-55453-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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