A Supervised Learning Approach to Construct Hyper-heuristics for Constraint Satisfaction.
José Carlos Ortiz-BaylissHugo Terashima-MarínSantiago Enrique Conant-PablosPublished in: MCPR (2013)
Keyphrases
- constraint satisfaction
- hyper heuristics
- constraint satisfaction problems
- supervised learning
- heuristic search
- constraint programming
- constraint propagation
- graph coloring
- combinatorial problems
- search space
- examination timetabling
- genetic programming
- arc consistency
- condition action rules
- phase transition
- non binary
- timetabling problem
- np complete
- search heuristics
- constraint solving
- constraint problems
- constraint relaxation
- evolutionary algorithm
- reinforcement learning
- constraint optimization
- constraint networks
- cutting stock problems
- np hard
- russian doll search
- machine learning
- learning algorithm
- robust fault detection
- soft constraints
- temporal constraints
- search strategies
- state space
- difficult problems
- constrained problems
- search procedure
- sat solvers
- lower bound
- objective function