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What to Predict for Efficient Scheduling on Parallel Machines

NeurIPS 2026 · Bandits and online learning › Online convex optimization and games · approach: Learning-augmented online algorithms

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Studies learning-augmented scheduling on parallel machines, where a noisy prediction encodes information about an optimal solution, for makespan and total weighted completion time objectives.

Problem

Scheduling on multiple parallel machines to minimize makespan or total weighted completion time when the algorithm receives a noisy prediction about an optimal solution.

Approach

Uses a solution encoding for predictions that implicitly quantifies both the amount of information provided and the nature of the prediction noise, rather than predicting job processing times alone.

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