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arxiv: 1907.03526 · v1 · pith:WQJI5LV5new · submitted 2019-07-08 · 💻 cs.CC · cs.DS

Inapproximability Results for Scheduling with Interval and Resource Restrictions

Pith reviewed 2026-05-25 00:44 UTC · model grok-4.3

classification 💻 cs.CC cs.DS
keywords restricted assignmentinterval restrictionsresource restrictionsinapproximabilityPTASmakespan minimizationSanta Claus problem
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The pith

Scheduling with interval eligibility has no PTAS unless P equals NP.

A machine-rendered reading of the paper's core claim, the machinery that carries it, and where it could break.

The paper studies the restricted assignment problem of assigning jobs to eligible machines to minimize the makespan. It focuses on two structured variants of eligibility constraints. For interval restrictions, where eligible machines form consecutive blocks, the work proves there is no polynomial-time approximation scheme. For resource restrictions with multiple capacities, it derives specific constant inapproximability thresholds.

Core claim

The restricted assignment problem with interval restrictions admits no PTAS unless P=NP. The resource-restricted variant admits no approximation ratio better than 48/47 with two resources and no better than 1.5 with four resources, unless P=NP. Both sets of results carry over to the corresponding Santa Claus maximization problems.

What carries the argument

NP-hardness reductions from known hard partitioning problems that encode the interval or resource constraints into job-machine eligibility while preserving the makespan objective.

If this is right

  • Interval eligibility does not suffice for a PTAS in restricted assignment.
  • Resource restrictions with two or four resources inherit constant-factor hardness.
  • The same inapproximability statements hold for the Santa Claus objective of maximizing the minimum machine load.

Where Pith is reading between the lines

These are editorial extensions of the paper, not claims the author makes directly.

  • Special cases known to have PTAS must exploit structure beyond mere intervals or low numbers of resources.
  • The reductions may adapt to show hardness for other objectives such as total completion time.
  • Parameterized algorithms could target the number of distinct intervals or resources as the parameter.

Load-bearing premise

That P is not equal to NP.

What would settle it

A polynomial-time algorithm that achieves an approximation ratio arbitrarily close to 1 for the interval-restricted problem on some infinite family of instances.

Figures

Figures reproduced from arXiv: 1907.03526 by Klaus Jansen, Marten Maack.

Figure 4
Figure 4. Figure 4: The left picture visualizes that each RAI instance can be seen as a RAR(2) instance and the right one depicts an RAR(2) instance that is not a RAI instance. In both pictures, each dimension corresponds to a resource, the squares mark the capacities of machines and the circles the demands of jobs. If the capacity of a machine is at least as big as the demand of a job in both dimension, the job is eligible o… view at source ↗
read the original abstract

In the restricted assignment problem, the input consists of a set of machines and a set of jobs each with a processing time and a subset of eligible machines. The goal is to find an assignment of the jobs to the machines minimizing the makespan, that is, the maximum summed up processing time any machine receives. Herein, jobs should only be assigned to those machines on which they are eligible. It is well-known that there is no polynomial time approximation algorithm with an approximation guarantee of less than 1.5 for the restricted assignment problem unless P=NP. In this work, we show hardness results for variants of the restricted assignment problem with particular types of restrictions. In the case of interval restrictions the machines can be totally ordered such that jobs are eligible on consecutive machines. We resolve the open question of whether the problem admits a polynomial time approximation scheme (PTAS) in the negative (unless P=NP). There are several special cases of this problem known to admit a PTAS. Furthermore, we consider a variant with resource restriction where each machine has capacities and each job demands for a fixed number of resources. A job is eligible on a machine if its demand is at most the capacity of the machine for each resource. For one resource, this problem is known to admit a PTAS, for two, the case of interval restrictions is contained, and in general, the problem is closely related to unrelated scheduling with a low rank processing time matrix. We show that there is no polynomial time approximation algorithm with a rate smaller than 48/47 or 1.5 for scheduling with resource restrictions with 2 or 4 resources, respectively, unless P=NP. All our results can be extended to the so called Santa Claus variants of the problems where the goal is to maximize the minimal processing time any machine receives.

Editorial analysis

A structured set of objections, weighed in public.

Desk editor's note, referee report, simulated authors' rebuttal, and a circularity audit. Tearing a paper down is the easy half of reading it; the pith above is the substance, this is the friction.

Referee Report

2 major / 2 minor

Summary. The paper studies inapproximability for the restricted assignment problem under two types of restrictions. For interval restrictions (machines ordered so that eligible machines for each job form an interval), it claims there is no PTAS unless P=NP, resolving an open question. For resource restrictions (machines have capacities per resource, jobs have demands), it claims inapproximability thresholds of 48/47 (2 resources) and 1.5 (4 resources) unless P=NP. All results extend to the Santa Claus maximization variants.

Significance. If the reductions are correct, the results are significant: they close the PTAS question for interval restrictions (noting that several special cases already admit PTASes) and give the first constant-factor hardness for the resource-restricted model with small numbers of resources, which is related to low-rank unrelated scheduling. The Santa Claus extensions broaden the applicability.

major comments (2)
  1. [interval restrictions section] The abstract asserts a negative PTAS result for interval restrictions, but a no-PTAS claim requires an approximation-preserving reduction that maps yes-instances to makespan ≤ B and no-instances to makespan ≥ (1+ε)B for some fixed ε>0 independent of n. The manuscript must exhibit this fixed-gap construction explicitly (rather than a plain NP-completeness reduction) in the interval-restrictions section; otherwise the resolution of the open question does not follow.
  2. [resource restrictions section] For the resource-restriction hardness results, the claimed ratios 48/47 (2 resources) and 1.5 (4 resources) must be shown to arise from gap-producing reductions; the manuscript should state the source problem, the gap value, and why the reduction is approximation-preserving in the relevant theorem statements.
minor comments (2)
  1. [abstract / introduction] The abstract mentions that 'several special cases of this problem known to admit a PTAS' but does not cite them; add references in the introduction.
  2. [Santa Claus variants paragraph] Notation for the Santa Claus variants should be introduced once and used consistently when stating the extensions of the hardness results.

Simulated Author's Rebuttal

2 responses · 0 unresolved

We thank the referee for the careful reading and constructive comments on our manuscript. We address the two major comments point by point below and will make the requested clarifications in the revised version.

read point-by-point responses
  1. Referee: [interval restrictions section] The abstract asserts a negative PTAS result for interval restrictions, but a no-PTAS claim requires an approximation-preserving reduction that maps yes-instances to makespan ≤ B and no-instances to makespan ≥ (1+ε)B for some fixed ε>0 independent of n. The manuscript must exhibit this fixed-gap construction explicitly (rather than a plain NP-completeness reduction) in the interval-restrictions section; otherwise the resolution of the open question does not follow.

    Authors: We thank the referee for highlighting this point. The reduction in Section 3 is an approximation-preserving reduction from a gap version of 3-Partition (or the appropriate source problem) that produces a fixed gap of 3/2 independent of n. To make this explicit as requested, we will revise the relevant theorem statement and add a short paragraph in the interval-restrictions section explaining the fixed gap and why the reduction is approximation-preserving. revision: yes

  2. Referee: [resource restrictions section] For the resource-restriction hardness results, the claimed ratios 48/47 (2 resources) and 1.5 (4 resources) must be shown to arise from gap-producing reductions; the manuscript should state the source problem, the gap value, and why the reduction is approximation-preserving in the relevant theorem statements.

    Authors: We agree that the theorem statements would benefit from greater explicitness. The 48/47 and 1.5 ratios are obtained from approximation-preserving reductions from known constant-factor inapproximability results for other scheduling problems. In the revised manuscript we will update the theorem statements for both the 2-resource and 4-resource cases to name the source problem, restate the exact gap values, and briefly note that the reductions preserve the approximation gap. revision: yes

Circularity Check

0 steps flagged

Standard reduction-based inapproximability; no circularity

full rationale

The paper establishes its central negative PTAS result for interval restrictions and the inapproximability bounds for resource restrictions exclusively via approximation-preserving reductions from externally known NP-complete problems. These reductions introduce fixed gaps independent of the target bounds and do not rely on self-definitional equations, fitted parameters renamed as predictions, or load-bearing self-citations whose validity depends on the present work. The derivation chain is therefore self-contained against external benchmarks and receives the default non-circularity finding.

Axiom & Free-Parameter Ledger

0 free parameters · 1 axioms · 0 invented entities

The results rest on the standard assumption P ≠ NP and on the existence of suitable NP-hard source problems for the reductions; no free parameters or invented entities appear in the abstract.

axioms (1)
  • domain assumption P ≠ NP
    Invoked to translate NP-hardness into inapproximability statements for both the interval and resource cases.

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