RL-GA: A Reinforcement Learning-based Genetic Algorithm for Electromagnetic Detection Satellite Scheduling Problem.
Yanjie SongLuona WeiQing YangJian WuLining XingYing-Wu ChenPublished in: Swarm Evol. Comput. (2023)
Keyphrases
- reinforcement learning
- genetic algorithm
- scheduling problem
- genetic algorithm ga
- tabu search
- learning classifier systems
- function approximation
- fitness function
- job shop scheduling problem
- model free
- simulated annealing
- multi objective
- metaheuristic
- reinforcement learning algorithms
- hybrid ga
- single machine
- hybrid genetic algorithm
- markov decision processes
- crossover and mutation
- evolutionary algorithm
- genetic operators
- parallel genetic algorithm
- learning algorithm
- evolutionary computation
- machine learning
- state space
- temporal difference
- control strategies
- optimization method
- mutation operator
- flowshop
- optimal policy
- multi agent
- direct policy search
- crossover operator
- hybrid algorithm
- job shop
- rl algorithms
- action space
- population size
- neural network
- reinforcement learning methods
- messy genetic algorithm
- temporal difference learning
- artificial neural networks
- particle swarm optimization pso
- np hard
- particle swarm optimization
- objective function
- optimal control
- genetic algorithm is employed
- minimizing makespan
- dynamic programming
- optimization problems
- genetic programming
- ant colony optimization
- remote sensing
- transfer learning
- learning problems
- initial population
- policy iteration