A Benchmarking Suite for Flexible Job Shop Scheduling Problems with Worker Flexibility under Uncertainty
402 standardized instances with worker flexibility and uncertainty simulation for scheduling solvers
The paper addresses the Flexible Job Shop Scheduling Problem (FJSP) and its extension with Worker Flexibility, which integrates workforce assignment into machine-operation scheduling. Existing solvers across Mathematical Programming, Constraint Programming, and Simulation-Based Optimization are often tailored to narrow use cases and validated on limited test sets, hindering cross-domain comparison. To overcome this, Hutter, Steinberger, and Hellwig introduce a comprehensive benchmarking environment built on 402 standardized FJSP instances, systematically extended to include worker flexibility. This creates a unique collection of ready-to-use worker flexibility instances, enabling rigorous, reproducible performance analysis.
The benchmark suite features multiple metrics for algorithm performance assessment, visualization of results, and state-of-the-art baseline results. By simulating uncertainties in processing times and resource availabilities, the environment supports development and evaluation of robust optimization strategies. The work lays a foundation for targeted algorithm development and consistent performance evaluation in production scheduling research, enabling fair comparison between solvers and scheduling subdomains.
- 402 standardized Flexible Job Shop Scheduling instances created for benchmarking
- Includes worker flexibility extension (workforce assignment) not previously available as a unified dataset
- Simulation-based uncertainty in processing times and resource availabilities enables robust strategy testing
Why It Matters
Standardized benchmarking with worker flexibility and uncertainty enables fair solver comparisons and robust production scheduling optimization.