Fair Repetitive Interval Scheduling
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Each of clients submits one job on every one of days. A job has a processing time and a due date, and — the schedule being just-in-time — occupies exactly the interval between them, so that on any single day the jobs a machine can accept are the ones whose intervals are pairwise disjoint. The objective is fairness rather than throughput: every client must be served on at least of the days. This submission formalizes the theorems of Heeger, Hermelin, Itzhaki, Molter and Shabtay on this problem, .
For , the problem is solvable in polynomial time when and NP-hard for every fixed pair with . Hardness already holds for and , with identical processing times. Under day-independent processing times it remains NP-hard and becomes a bipartite matching problem when the processing times are one. Under day-independent due dates it remains NP-hard, and becomes tractable either for a constant number of days, by a dynamic program over the clients in due-date order, or for day-independent processing times, where a -fair schedule exists exactly when times the chromatic number of the one conflict graph is at most . Measured against the treewidth of the overall conflict graph, the problem is NP-hard for constant , fixed-parameter tractable for , and fixed-parameter tractable for .
Every gadget construction is given explicitly, with numbered clients and days, and each statement about it is separate: that the construction is correct, that the instance it produces has the structure claimed of it, and that it is computed within the stated resources. The two objectives — the uniform one and the per-client generalization , through which the treewidth reduction passes — are one definition, the uniform case being the constant one. Hardness is stated against the class NP of the archive; treewidth is the archive's, and the tree decompositions the dynamic program of the treewidth algorithm runs on are nice ones in the sense of Kloks.
The formalization adjusts the placement of inactive jobs to preserve the conflict graph required by the treewidth argument. On each gadget day, the dummy client's interval covers a region containing a separate, disjoint slot for every inactive client. This preserves the blocking argument without introducing conflicts between inactive clients. The concept pages specify the construction and its tree decomposition.
6 pages · 24 marked passages
Concepts
- cor✓
BipartiteDecision - thm✓
BipartiteKuhnCorrect - thm✓
BipartiteKuhnTime - def✓
Bodlaender - thm✓
BodlaenderGeneral - thm✓
BodlaenderKloks - def✓
BoundedSat - def✓
ConflictGraph - cor✓
Corollary8 - lem✓
ExtremeFairness - def✓
IlpClients - def✓
InstanceEncoding - def✓
JustInTime - lem✓
Lemma14 - lem✓
Lemma15 - def✓
MulticolouredIndepSet - def✓
Problems - thm✓
Theorem1 - thm✓
Theorem10 - thm✓
Theorem11 - thm✓
Theorem12 - thm✓
Theorem13 - thm✓
Theorem2 - thm✓
Theorem3 - thm✓
Theorem4 - thm✓
Theorem7 - thm✓
Theorem9 - thm✓
TwoSatCorrectness - lem✓
TwoSatCriterion - thm✓
TwoSatInP - def✓
TwoSatisfiability - thm✓
TwoSatRunningTime
- def
BipartiteGraph - def
BipartiteKuhn - def
BipartiteMatching - def
GraphWords - def
ParameterizedComplexity - def
Scheduling - def
TwoSatAlgorithm - def
TwoSatCNF - def
TwoSatImplicationGraph
- lem✓
Lax429075.EncodingCorrect - lem✓
Lax429075.SATHard - def✓
Lax434930.Certificates - thm✓
Lax759944.TuringRamPolytimeEquivalence
- def
Lax228581.Treewidth - def
Lax271696.GraphEncoding - def
Lax429075.CNF - def
Lax429075.Encoding - def
Lax429075.Reductions - def
Lax429075.Satisfiability - def
Lax434930.NondeterministicPolynomialTime - def
Lax434930.PolynomialTime - def
Lax759944.BinaryWordEncoding - def
Lax759944.RamPolytime - def
Lax759944.TuringPolytime - def
Lax808846.Ram - def
Lax808846.RamComputes
Concept map
Proofs
Proof networkview on GitHub
Proof list
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⊢
Lax117284Proofs.Bipartite.MachineTotal.decides_saturating_all -
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Lax117284Proofs.Bipartite.MachineTotal.ramPolytime_saturating -
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Lax117284Proofs.BodlaenderProved.niceDecomposition_computable_proved -
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Lax117284Proofs.ExtremeFairness.not_hasKFairSchedule_of_days_lt -
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Lax117284Proofs.Machine.BlockFinal.reduceBlockingDay_polyTime -
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Lax117284Proofs.McisHard.normalMulticolouredIndepSet_npHard_proved -
⊢
Lax117284Proofs.Theorem3Colouring.uniform_dayIndepD_dayIndepP_mem_P -
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Lax117284Proofs.Theorem4ClientsReduction.byClients_fptReduces_ilp -
⊢
Lax117284Proofs.Tractable.hasKFairSchedule_iff_hasFullMatching -
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Lax117284Proofs.Tractable.hasKFairSchedule_iff_mul_chromaticNumber_le -
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Lax117284Proofs.Tractable.hasKFairSchedule_iff_mul_cliqueNum_le -
⊢
Lax117284Proofs.Treewidth.Fun.Final.improveDecomposition_proved -
⊢
Lax117284Proofs.Treewidth.Fun.Final.niceDecomposition_computable_proved
Lean sources for these proofs: proofs/ on GitHub
Proof code is not displayed; the archive records each proof's checked relationship between claims.
Related submissions
Submission map
Cite this
This is only the formalizers. The authors of the formalized results may be different (see References).
@misc{lax-117284,
author = {Yuval Itzhaki and Claude},
title = {Fair Repetitive Interval Scheduling},
year = {2026},
howpublished = {Lax Archive, lax-117284},
url = {https://laxarchive.org/lax-117284/},
note = {draft},
}
References
- Klaus Heeger, Danny Hermelin, Yuval Itzhaki, Hendrik Molter and Dvir Shabtay. Fair Repetitive Interval Scheduling. Algorithmica, 2025. doi:10.1007/s00453-025-01322-y
- Craig A. Tovey. A Simplified NP-Complete Satisfiability Problem. Discrete Applied Mathematics 8(1):85–89, 1984.
- Shao Chin Sung and Milan Vlach. Maximizing Weighted Number of Just-in-Time Jobs on Unrelated Parallel Machines. Journal of Scheduling 8(5):453–460, 2005.
- Krzysztof Pietrzak. On the Parameterized Complexity of the Fixed Alphabet Shortest Common Supersequence and Longest Common Subsequence Problems. Journal of Computer and System Sciences 67(4):757–771, 2003.
- Michael R. Fellows, Danny Hermelin, Frances Rosamond and Stéphane Vialette. On the Parameterized Complexity of Multiple-Interval Graph Problems. Theoretical Computer Science 410(1):53–61, 2009.
- Bengt Aspvall, Michael F. Plass and Robert E. Tarjan. A Linear-Time Algorithm for Testing the Truth of Certain Quantified Boolean Formulas. Information Processing Letters 8(3):121–123, 1979.
- John E. Hopcroft and Richard M. Karp. An Algorithm for Maximum Matchings in Bipartite Graphs. SIAM Journal on Computing 2(4):225–231, 1973.
- Hans L. Bodlaender. A Linear-Time Algorithm for Finding Tree-Decompositions of Small Treewidth. SIAM Journal on Computing 25(6):1305–1317, 1996.
- Ton Kloks. Treewidth: Computations and Approximations. Springer 842, 1994.
- Hans L. Bodlaender and Ton Kloks. Efficient and Constructive Algorithms for the Pathwidth and Treewidth of Graphs. Journal of Algorithms 21(2):358–402, 1996.
- Ernst Althaus and Sarah Ziegler. Optimal Tree Decompositions Revisited: A Simpler Linear-Time FPT Algorithm. arXiv:1912.09144, 2020.
- Martin Charles Golumbic. Algorithmic Graph Theory and Perfect Graphs. Academic Press, 1980.
- Harold W. Kuhn. The Hungarian Method for the Assignment Problem. Naval Research Logistics Quarterly 2(1–2):83–97, 1955.
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