Learning Priority Indices for Energy-Aware Scheduling of Jobs on Batch Processing Machines
Daniel Sascha Schorn, Lars Mönch
Abstract
A scheduling problem for parallel batch processing machines (BPMs) with jobs having unequal ready times in semiconductor wafer fabrication facilities (wafer fabs) is studied in this paper. A blended objective function combining the total weighted tardiness (TWT) and the total electricity cost (TEC) under a time-of-use (TOU) tariff is considered. A genetic programming (GP) procedure is designed to automatically discover priority indices for a heuristic scheduling framework. Results of computational experiments are reported that demonstrate that the learned priority indices lead to high-quality schedules in a short amount of computing time.
Topics & Concepts
TardinessWafer fabricationScheduling (production processes)Computer scienceJob shop schedulingSemiconductor device fabricationElectricityBatch processingJob schedulerIndustrial engineeringWaferMathematical optimizationEngineeringEmbedded systemOperating systemElectrical engineeringRouting (electronic design automation)MathematicsCloud computingScheduling and Optimization AlgorithmsEvolutionary Algorithms and ApplicationsMetaheuristic Optimization Algorithms Research