Learning effective dispatching rules for batch processor scheduling
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Publication:5385460
DOI10.1080/00207540600993360zbMath1160.90392OpenAlexW2037705289MaRDI QIDQ5385460
Reha Uzsoy, Christopher D. Geiger
Publication date: 6 May 2008
Published in: International Journal of Production Research (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1080/00207540600993360
Deterministic scheduling theory in operations research (90B35) Approximation methods and heuristics in mathematical programming (90C59) Production models (90B30)
Related Items (4)
Genetic programming-based hyper-heuristic approach for solving dynamic job shop scheduling problem with extended technical precedence constraints ⋮ Learning-augmented heuristics for scheduling parallel serial-batch processing machines ⋮ A memetic algorithm for minimizing total weighted tardiness on parallel batch machines with incompatible job families and dynamic job arrival ⋮ A survey of scheduling with parallel batch (p-batch) processing
Cites Work
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- Efficient scheduling algorithms for a single batch processing machine
- Minimizing total completion time on a batch processing machine with job families
- Batching and Scheduling Jobs on Batch and Discrete Processors
- Efficient Algorithms for Scheduling Semiconductor Burn-In Operations
- Job shop scheduling with a genetic algorithm and machine learning
- Dynamic scheduling selection of dispatching rules for manufacturing system
- Minimizing makespan on a single batch processing machine with dynamic job arrivals
- Control of a batch-processing machine: A computational approach
- Scheduling batch processing machines with incompatible job families
- A learning-based methodology for dynamic scheduling in distributed manufacturing systems
- Genetic algorithm based scheduling of parallel batch machines with incompatible job families to minimize total weighted tardiness
- Selection of dispatching rules on multiple dispatching decision points in real-time scheduling of a semiconductor wafer fabrication system
- Scheduling Groups of Jobs on a Single Machine
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