Multi-objective energy-efficient hybrid flow shop scheduling using Q-learning and GVNS driven NSGA-II.
Peize LiQiang XueZiteng ZhangJian ChenDequn ZhouPublished in: Comput. Oper. Res. (2023)
Keyphrases
- energy efficient
- multi objective
- nsga ii
- multi objective optimization
- wireless sensor networks
- multiobjective optimization
- pareto optimal
- multiobjective evolutionary algorithm
- evolutionary algorithm
- energy consumption
- optimization algorithm
- multi objective optimization problems
- sensor networks
- multi objective evolutionary algorithms
- bi objective
- multi agent
- particle swarm optimization
- multi objective optimisation
- multiple objectives
- energy efficiency
- base station
- evolutionary multiobjective optimization
- crossover operator
- genetic algorithm
- pareto dominance
- test problems
- reinforcement learning
- cooperative
- routing protocol
- pareto optimal solutions
- evolutionary multiobjective
- objective function
- multi objective problems
- scheduling problem
- multi criteria
- strength pareto evolutionary algorithm
- computational complexity
- optimization problems
- hybrid genetic algorithm
- differential evolution
- pareto frontier
- neural network
- routing algorithm
- dynamic programming
- evolutionary computation
- optimal solution
- data transmission