Small feedforward neural networks embedded in MILP surgical scheduling models deliver the fastest solutions with optimality gaps below 2%, highest utilization in most cases, and simulated overtime closest to targets on hospital data.
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Handling Overtime Constraints in Mixed Integer Linear Programming for Surgical Scheduling: A Comparison of Neural Network and Classical Linearization Techniques
Small feedforward neural networks embedded in MILP surgical scheduling models deliver the fastest solutions with optimality gaps below 2%, highest utilization in most cases, and simulated overtime closest to targets on hospital data.