An End-to-End Reinforcement Learning Approach for Job-Shop Scheduling Problems Based on Constraint Programming.
Pierre TasselMartin GebserKonstantin SchekotihinPublished in: ICAPS (2023)
Keyphrases
- end to end
- constraint programming
- job shop scheduling problem
- reinforcement learning
- job shop scheduling
- particle swarm algorithm
- constraint satisfaction problems
- scheduling problem
- constraint propagation
- combinatorial problems
- tabu search
- memetic algorithm
- genetic algorithm
- constraint satisfaction
- search strategies
- benchmark problems
- symmetry breaking
- graph model
- simulated annealing
- hard and soft constraints
- machine learning
- global constraints
- constraint solving
- congestion control
- combinatorial optimization problems
- state space
- dynamic programming
- special case
- optimal policy
- metaheuristic
- combinatorial optimization