A Q-Learning Proposal for Tuning Genetic Algorithms in Flexible Job Shop Scheduling Problems.
Christian PérezCarlos MarchMiguel A. SalidoPublished in: FLAIRS (2023)
Keyphrases
- job shop scheduling problem
- genetic algorithm
- job shop scheduling
- memetic algorithm
- tabu search
- simulated annealing
- particle swarm algorithm
- scheduling problem
- genetic operators
- artificial immune system
- reinforcement learning
- benchmark problems
- function approximation
- multi agent
- fitness function
- metaheuristic
- credit assignment
- multi objective
- combinatorial optimization problems
- particle swarm optimization
- particle swarm optimisation
- evolutionary algorithm
- graph model
- genetic programming
- state space
- hybrid algorithm
- differential evolution
- genetic algorithm ga
- artificial neural networks
- learning algorithm
- neural network
- multi objective optimization
- test problems
- evolutionary computation
- mutation operator
- lower bound
- search algorithm
- ant colony optimization