David Hutter, Thomas Steinberger, Michael Hellwig
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.