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arxiv: 2501.16159 · v3 · submitted 2025-01-27 · 💻 cs.NE

A Benchmarking Suite for Flexible Job Shop Scheduling Problems with Worker Flexibility under Uncertainty

David Hutter , Thomas Steinberger , Michael Hellwig This is my paper

Pith reviewed 2026-05-23 04:49 UTC · model grok-4.3

classification 💻 cs.NE
keywords flexible job shop schedulingworker flexibilitybenchmarking suiteuncertainty simulationproduction schedulingoptimization solversrobust optimization
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The pith

A new benchmarking suite extends 402 standard flexible job shop instances to include worker flexibility and uncertainty.

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

The paper builds a ready-to-use collection of worker-flexibility scheduling problems by taking 402 existing standardized flexible job shop instances and adding workforce assignment and uncertainty simulation. It supplies performance metrics, result visualizations, and baseline solver results so that algorithms from mathematical programming, constraint programming, and simulation-based optimization can be compared directly. The environment is intended to support reproducible tests of robust strategies when processing times or resource availability vary. Researchers gain a common testbed that spans scheduling subdomains without having to create their own instances from scratch.

Core claim

The paper creates a hitherto unique collection of ready-to-use worker flexibility instances by systematically extending 402 standardized Flexible Job Shop Scheduling Problem instances. The resulting benchmark suite supplies several metrics for algorithm performance assessment, visualization of algorithmic results, and state-of-the-art baseline results, thereby enabling rigorous, reproducible, and comparable performance analysis between solvers and scheduling problem subdomains. Through simulation-based integration of uncertainties in processing times and resource availabilities, the environment supports development and evaluation of robust optimization strategies.

What carries the argument

The benchmarking suite that systematically extends 402 FJSP instances with worker flexibility and uncertainty simulation.

If this is right

  • Solvers from mathematical programming, constraint programming, and simulation-based optimization can be evaluated on identical worker-flexibility problems.
  • Robust strategies can be tested against simulated changes in processing times and resource availability.
  • Algorithm results can be assessed with standardized metrics and visualized for direct comparison.
  • New algorithms for production scheduling can be validated against provided state-of-the-art baselines.

Where Pith is reading between the lines

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

  • The suite could be used to identify which solver domains handle worker flexibility most efficiently under uncertainty.
  • Manufacturers might adopt the instances as standard test cases when evaluating scheduling software for flexible workforces.
  • Future extensions could add more uncertainty types while keeping the same base instances for longitudinal comparisons.

Load-bearing premise

The 402 standardized FJSP instances can be systematically extended to include worker flexibility while remaining representative and useful for cross-domain solver comparison and uncertainty simulation.

What would settle it

Running the same set of solvers on the new worker-flexibility instances and finding that performance rankings differ sharply from their rankings on the original FJSP instances without worker flexibility would indicate the extensions do not preserve comparability.

Figures

Figures reproduced from arXiv: 2501.16159 by David Hutter, Michael Hellwig, Thomas Steinberger.

Figure 1
Figure 1. Figure 1: Visualization of the problem classes in the area of Production Scheduling considered in this paper. [PITH_FULL_IMAGE:figures/full_fig_p003_1.png] view at source ↗
Figure 2
Figure 2. Figure 2: Explanation of the standard FJSSP benchmark specifications on the basis of the 11th test instance [PITH_FULL_IMAGE:figures/full_fig_p010_2.png] view at source ↗
Figure 3
Figure 3. Figure 3: An overview over the benchmark instances on a subset of problem characteristics to show the [PITH_FULL_IMAGE:figures/full_fig_p011_3.png] view at source ↗
Figure 4
Figure 4. Figure 4: Explanation of the FJSSP-W benchmark specifications based on an extended FJSSP test instance. [PITH_FULL_IMAGE:figures/full_fig_p016_4.png] view at source ↗
Figure 5
Figure 5. Figure 5: Illustration of the distribution of benchmark instances with respect to their flexibility [PITH_FULL_IMAGE:figures/full_fig_p019_5.png] view at source ↗
Figure 6
Figure 6. Figure 6: An example plot using example data displaying the portion of instances that lie within a certain [PITH_FULL_IMAGE:figures/full_fig_p020_6.png] view at source ↗
Figure 7
Figure 7. Figure 7: A Nemenyi diagram based on the example data using 4 solvers for 402 problems. [PITH_FULL_IMAGE:figures/full_fig_p021_7.png] view at source ↗
Figure 8
Figure 8. Figure 8: Illustration of the progress (7) of the example solvers on a specific problem. Part (a) displays the [PITH_FULL_IMAGE:figures/full_fig_p022_8.png] view at source ↗
Figure 9
Figure 9. Figure 9: The δrel for the FJSSP-W on benchmark instances for the solvers used for the comparison of the approaches is shown in (a). In (b), the Nemenyi diagram for the used solvers is depicted showing the average rankings of each solver. The table in (c) shows the MiniZinc score achieved by the compared solvers. 5.1. Experimental Settings For the FJSSP-W, the solvers were tasked with solving all 402 benchmarks. The… view at source ↗
read the original abstract

This paper addresses the Flexible Job Shop Scheduling Problem and its extension with Worker Flexibility, which integrates workforce assignment into machine-operation scheduling. Diverse solvers have been proposed across multiple optimization domains including Mathematical Programming, Constraint Programming, and Simulation-Based Optimization, or Simulation-based Optimization. These are often tailored to narrow use cases and validated on limited test problem sets, hindering cross-domain comparison. To overcome this, a comprehensive benchmarking environment built on 402 standardized Flexible Job Shop Scheduling Problem instances is introduced and systematically extended to include worker flexibility. This creates a hitherto unique collection of ready-to-use worker flexibility instances. The benchmark suite features several metrics for algorithm performance assessment, the visualization of algorithmic results, as well as state-of-the-art baseline results. This enables rigorous, reproducible, and comparable performance analysis between solvers and scheduling problem subdomains. Through the simulation-based integration of uncertainties in processing times as well as resource availabilities, the environment supports the development and evaluation of robust optimization strategies. The present work lays a foundation for targeted algorithm development and consistent performance evaluation in production scheduling research.

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

1 major / 0 minor

Summary. The manuscript introduces a benchmarking suite for the Flexible Job Shop Scheduling Problem (FJSP) with worker flexibility under uncertainty. It extends 402 standardized FJSP instances to include worker flexibility, supplies performance metrics, visualizations of results, state-of-the-art baselines, and simulation-based support for uncertainties in processing times and resource availabilities, with the goal of enabling rigorous, reproducible, and comparable evaluations across solvers from different optimization domains.

Significance. If the extension procedure is sound and the instances remain representative, the work supplies a useful infrastructure contribution by creating a previously unavailable collection of ready-to-use worker-flexibility instances together with standardized evaluation tools. This could facilitate cross-domain comparisons and robust optimization research in production scheduling.

major comments (1)
  1. [Abstract] Abstract: the description of benchmark construction supplies no details on instance generation, validation procedures, or baseline computation methods, preventing verification that the systematic extension of the 402 instances remains representative for cross-domain solver comparison and uncertainty simulation.

Simulated Author's Rebuttal

1 responses · 0 unresolved

We thank the referee for the constructive feedback and positive assessment of the work's potential contribution. We address the single major comment below.

read point-by-point responses

  1. Referee: [Abstract] Abstract: the description of benchmark construction supplies no details on instance generation, validation procedures, or baseline computation methods, preventing verification that the systematic extension of the 402 instances remains representative for cross-domain solver comparison and uncertainty simulation.

    Authors: We agree the abstract is high-level and omits these specifics. The full manuscript details the systematic extension of the 402 instances in Section 3 (including how worker flexibility and uncertainty parameters were added while preserving original problem characteristics), validation via statistical property checks in Section 3.3, and baseline solver computations (CP, MIP, and metaheuristics) in Sections 5 and 6. To improve accessibility, we will revise the abstract to briefly reference the extension method and validation steps. revision: yes

Circularity Check

0 steps flagged

No significant circularity

full rationale

The paper presents an infrastructural contribution: the systematic extension of 402 existing standardized FJSP instances to worker flexibility, plus metrics, visualizations, baselines, and uncertainty simulation support. No derivation, parameter fitting, or theorem is claimed; the central claim is the creation of a ready-to-use benchmark collection. No self-citation load-bearing steps, no self-definitional reductions, and no fitted inputs presented as predictions appear in the provided text. The work is self-contained against external standardized instances.

Axiom & Free-Parameter Ledger

0 free parameters · 0 axioms · 0 invented entities

This is an applied benchmarking and tool paper rather than a theoretical derivation; no free parameters, mathematical axioms, or invented entities are introduced.

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Reference graph

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