Solving energy-efficient fuzzy hybrid flow-shop scheduling problem at a variable machine speed using an extended NSGA-II.
Yi-Jian WangGai-Ge WangFang-Ming TianDun-Wei GongWitold PedryczPublished in: Eng. Appl. Artif. Intell. (2023)
Keyphrases
- energy efficient
- nsga ii
- multi objective
- wireless sensor networks
- multi objective optimization
- evolutionary algorithm
- pareto dominance
- pareto optimal
- energy consumption
- test problems
- multiobjective optimization
- multiobjective evolutionary algorithm
- base station
- sensor networks
- optimization problems
- evolutionary multiobjective optimization
- optimization algorithm
- multi objective differential evolution
- evolutionary multiobjective
- optimal solution
- multi objective evolutionary algorithms
- energy efficiency
- high speed
- multi objective optimization problems
- differential evolution
- fuzzy logic
- knapsack problem
- constrained multi objective optimization problems
- routing protocol
- data sets
- fitness function
- routing algorithm
- bi objective
- multi criteria
- genetic algorithm
- particle swarm optimization
- multi core architecture
- combinatorial optimization
- sensor data
- genetic programming
- upper bound
- lower bound
- objective function
- neural network