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DOI: 10.4230/LIPIcs.IPEC.2025.7

Parameterized Complexity of Scheduling Unit-Time Jobs with Generalized Precedence Constraints

Authors: Christina Büsing, Maurice Draeger, and Corinna Mathwieser

Published in: LIPIcs, Volume 358, 20th International Symposium on Parameterized and Exact Computation (IPEC 2025)

Abstract

We study the parameterized complexity of scheduling unit-time jobs on parallel, identical machines under generalized precedence constraints for minimization of the makespan and the sum of completion times (P|gen-prec, p_j = 1|γ, γ ∈ {C_max,∑_jC_j}). In our setting, each job is equipped with a Boolean formula (precedence constraint) over the set of jobs. A schedule satisfies a job’s precedence constraint if setting earlier jobs to true satisfies the formula. Our definition generalizes several common types of precedence constraints: classical and-constraints if every formula is a conjunction, or-constraints if every formula is a disjunction, and and/or-constraints if every formula is in conjunctive normal form. We prove fixed-parameter tractability when parameterizing by the number of predecessors. For parameterization by the number of successors, however, the complexity depends on the structure of the precedence constraints. If every constraint is a conjunction or a disjunction, we prove the problem to be fixed-parameter tractable. For constraints in disjunctive normal form, we prove W[1]-hardness. We show that the and/or-constrained problem is NP-hard, even for a single successor. Moreover, we prove NP-hardness on two machines if every constraint is a conjunction or a disjunction. This result not only proves para-NP-hardness for parameterization by the number of machines but also complements the polynomial-time solvability on two machines if every constraint is a conjunction [Coffman and Graham, 1972] or if every constraint is a disjunction [Johannes, 2005].

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Christina Büsing, Maurice Draeger, and Corinna Mathwieser. Parameterized Complexity of Scheduling Unit-Time Jobs with Generalized Precedence Constraints. In 20th International Symposium on Parameterized and Exact Computation (IPEC 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 358, pp. 7:1-7:16, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{busing_et_al:LIPIcs.IPEC.2025.7,
  author =	{B\"{u}sing, Christina and Draeger, Maurice and Mathwieser, Corinna},
  title =	{{Parameterized Complexity of Scheduling Unit-Time Jobs with Generalized Precedence Constraints}},
  booktitle =	{20th International Symposium on Parameterized and Exact Computation (IPEC 2025)},
  pages =	{7:1--7:16},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-407-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{358},
  editor =	{Agrawal, Akanksha and van Leeuwen, Erik Jan},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.IPEC.2025.7},
  URN =		{urn:nbn:de:0030-drops-251390},
  doi =		{10.4230/LIPIcs.IPEC.2025.7},
  annote =	{Keywords: scheduling, precedence constraints, fixed-parameter tractability, complexity}
}

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DOI: 10.4230/LIPIcs.ESA.2025.112

A Faster Parametric Search for the Integral Quickest Transshipment Problem

Authors: Mariia Anapolska, Dario van den Boom, Christina Büsing, and Timo Gersing

Published in: LIPIcs, Volume 351, 33rd Annual European Symposium on Algorithms (ESA 2025)

Abstract

Algorithms for computing fractional solutions to the quickest transshipment problem have been significantly improved since Hoppe and Tardos first solved the problem in strongly polynomial time. For integral solutions, however, no structural improvements on their algorithm itself have yet been proposed. Runtime improvements are limited to general progress on submodular function minimization (SFM), which is an integral part of Hoppe and Tardos' algorithm. In fact, SFM constitutes the main computational load of the algorithm, as the runtime is blown up by using it within Megiddo’s parametric search algorithm. We replace this part of Hoppe and Tardos' algorithm with a more efficient routine that solves only a linear number of SFM and, in contrast to previous techniques, exclusively uses minimum cost flow algorithms within Megiddo’s parametric search. Our approach improves the state-of-the-art runtime from 𝒪̃(m⁴ k^15) down to 𝒪̃(m²k⁵ + m⁴ k²), where k is the number of terminals and m is the number of arcs.

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Mariia Anapolska, Dario van den Boom, Christina Büsing, and Timo Gersing. A Faster Parametric Search for the Integral Quickest Transshipment Problem. In 33rd Annual European Symposium on Algorithms (ESA 2025). Leibniz International Proceedings in Informatics (LIPIcs), Volume 351, pp. 112:1-112:15, Schloss Dagstuhl – Leibniz-Zentrum für Informatik (2025)

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@InProceedings{anapolska_et_al:LIPIcs.ESA.2025.112,
  author =	{Anapolska, Mariia and van den Boom, Dario and B\"{u}sing, Christina and Gersing, Timo},
  title =	{{A Faster Parametric Search for the Integral Quickest Transshipment Problem}},
  booktitle =	{33rd Annual European Symposium on Algorithms (ESA 2025)},
  pages =	{112:1--112:15},
  series =	{Leibniz International Proceedings in Informatics (LIPIcs)},
  ISBN =	{978-3-95977-395-9},
  ISSN =	{1868-8969},
  year =	{2025},
  volume =	{351},
  editor =	{Benoit, Anne and Kaplan, Haim and Wild, Sebastian and Herman, Grzegorz},
  publisher =	{Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik},
  address =	{Dagstuhl, Germany},
  URL =		{https://drops.dagstuhl.de/entities/document/10.4230/LIPIcs.ESA.2025.112},
  URN =		{urn:nbn:de:0030-drops-245817},
  doi =		{10.4230/LIPIcs.ESA.2025.112},
  annote =	{Keywords: Flow over time, dynamic transshipment, quickest transshipment, parametric submodular functions, efficient algorithms}
}

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Parameterized Complexity of Scheduling Unit-Time Jobs with Generalized Precedence Constraints

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A Faster Parametric Search for the Integral Quickest Transshipment Problem

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