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Modelling and Solving the Minimum Shift Design Problem

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Integration of Constraint Programming, Artificial Intelligence, and Operations Research (CPAIOR 2019)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 11494))

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Abstract

When demand for employees varies throughout the day, the minimum shift design (MSD) problem aims at placing a minimum number of shifts that cover the demand with minimum overstaffing and understaffing. This paper investigates different constraint models for the problem, using a direct representation, a counting representation and a network flow based model and applies both constraint programming (CP) and mixed integer programming (MIP) solvers. The results show that the model based on network flow clearly outperforms the other models. While a CP solver finds some optimal results, with MIP solvers it can for the first time provide optimal solutions to all existing benchmark instances in short computational time.

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Notes

  1. 1.

    http://www.dbai.tuwien.ac.at/proj/Rota/benchmarks.html.

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Acknowledgements

The financial support by the Austrian Federal Ministry for Digital and Economic Affairs and the National Foundation for Research, Technology and Development is gratefully acknowledged.

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Authors and Affiliations

  1. Christian Doppler Laboratory for Artificial Intelligence and Optimization for Planning and Scheduling, DBAI, TU Wien, Vienna, Austria

    Lucas Kletzander & Nysret Musliu

Authors
  1. Lucas Kletzander
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  2. Nysret Musliu
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Corresponding author

Correspondence to Lucas Kletzander .

Editor information

Editors and Affiliations

  1. Ecole Polytechnique de Montréal, Montréal, QC, Canada

    Louis-Martin Rousseau

  2. University of Western Macedonia, Kozani, Greece

    Kostas Stergiou

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Kletzander, L., Musliu, N. (2019). Modelling and Solving the Minimum Shift Design Problem. In: Rousseau, LM., Stergiou, K. (eds) Integration of Constraint Programming, Artificial Intelligence, and Operations Research. CPAIOR 2019. Lecture Notes in Computer Science(), vol 11494. Springer, Cham. https://doi.org/10.1007/978-3-030-19212-9_26

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  • DOI: https://doi.org/10.1007/978-3-030-19212-9_26

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  • Online ISBN: 978-3-030-19212-9

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