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Repairing Schedules by Removing Waiting Times: A Parameterized Complexity Analysis

Authors Niels Grüttemeier , Klaus Heeger

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Subject Classification

ACM Subject Classification
  • Theory of computation → Parameterized complexity and exact algorithms
  • Theory of computation → Problems, reductions and completeness
  • Mathematics of computing → Combinatorics
Keywords
  • Job shop
  • parallel machines
  • reactive scheduling

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Abstract

We consider the problem of repairing production schedules in a job-shop setting by reducing pre-planned waiting times. Herein, a schedule of all jobs is given. To compensate unforeseen disturbances, this schedule contains waiting times between the execution of two consecutive tasks of a job. Further, we assume that the schedule temporarily overloads some machines, e.g. due to reduced machine capacities because of worker sickness or (partially) broken machines. We study the problem of removing as few waiting times as possible in order to eliminate the machine overloads. After formalizing this problem, we perform an extensive analysis of its parameterized complexity with respect to several natural parameters, resulting in a detailed picture of the problem’s complexity.

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Niels Grüttemeier and Klaus Heeger. Repairing Schedules by Removing Waiting Times: A Parameterized Complexity Analysis. In 19th International Symposium on Algorithms and Data Structures (WADS 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 349, pp. 31:1-31:14, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025) https://doi.org/10.4230/LIPIcs.WADS.2025.31

Author Details

Niels Grüttemeier
  • Fraunhofer IOSB-INA, Lemgo, Germany
Klaus Heeger
  • Fraunhofer IOSB-INA, Lemgo, Germany

Funding

  • Grüttemeier, Niels: Supported by the project Datenfabrik.NRW, a project by KI.NRW, funded by the Ministry for Economics, Innovation, Digitalization and Energy of the State of North Rhine-Westphalia (MWIDE).
  • Heeger, Klaus: Supported by the German Federal Ministry for the Environment, Nature Conservation, Nuclear Safety and Consumer Protection (BMUV) under the project Smart-E-Factory.

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