Proactive Algorithms for Job Shop Scheduling with Probabilistic Durations
Session date: 30 June 2025
Session host: Konstantin Sidorov
Summary:
We looked at a variety of papers on scheduling in this seminar series; however, the common assumption underpinning them is that the problem data is deterministic, for example, that the task durations do not fluctuate during the plan execution. In this session, I want to review a paper that lifts this assumption and design a branch-and-bound algorithm that uses Monte Carlo estimates in place of “deterministic” pruning.
Relevant papers
- Proactive Algorithms for Job Shop Scheduling with Probabilistic DurationsJournal of Artificial Intelligence Research, Mar 2007