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Balancing Schedules Using Maximum Leximin

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Symbolic and Quantitative Approaches to Reasoning with Uncertainty (ECSQARU 2019)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 11726))

Abstract

We consider the problem of assigning, in a fair way, time limits for processes in manufacturing a product, subject to a deadline where the duration of each activity can be uncertain. We focus on an approach based on choosing the maximum element according to a leximin ordering, and we prove the correctness of a simple iterative procedure for generating this maximally preferred element. Our experimental testing illustrates the efficiency of our approach.

This material is based upon works supported by the Science Foundation Ireland under Grant No. 12/RC/2289 which is co-funded under the European Regional Development Fund, and by United Technologies Corporation under the Insight-UCC Collaboration Project.

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Notes

  1. 1.

    This is different from the classic water pouring/filling algorithms for allocating power [17].

  2. 2.

    For space reasons, almost all the proofs have been omitted; they can be found in the longer version  [20], which also contains auxiliary results and many more details about the implementation and experimental testing.

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Authors and Affiliations

  1. Insight Centre for Data Analytics, School of CS and IT, University College Cork, Cork, Ireland

    Federico Toffano & Nic Wilson

Authors
  1. Federico Toffano
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  2. Nic Wilson
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Correspondence to Nic Wilson .

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Editors and Affiliations

  1. Technische Universität Dortmund, Dortmund, Germany

    Gabriele Kern-Isberner

  2. Mathematical Institute of the Serbian Academy of Sciences and Arts, Belgrade, Serbia

    Zoran Ognjanović

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Toffano, F., Wilson, N. (2019). Balancing Schedules Using Maximum Leximin. In: Kern-Isberner, G., Ognjanović, Z. (eds) Symbolic and Quantitative Approaches to Reasoning with Uncertainty. ECSQARU 2019. Lecture Notes in Computer Science(), vol 11726. Springer, Cham. https://doi.org/10.1007/978-3-030-29765-7_41

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  • DOI: https://doi.org/10.1007/978-3-030-29765-7_41

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-29764-0

  • Online ISBN: 978-3-030-29765-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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