Adaptive engine optimisation using NSGA-II and MODA based on a sub-structured artificial neural network.
Songshan GuoMark DoonerJihong WangHongming XuGuoxiang LuPublished in: ICAC (2017)
Keyphrases
- nsga ii
- multi objective optimisation
- multi objective
- artificial neural networks
- genetic algorithm
- multi objective optimization
- test problems
- evolutionary algorithm
- multiobjective optimization
- pareto optimal
- optimization problems
- evolutionary multiobjective
- evolutionary multiobjective optimization
- multi objective differential evolution
- differential evolution
- multiobjective evolutionary algorithm
- optimization algorithm
- neural network
- test functions
- knapsack problem
- optimal solution
- mutation operator
- uniform design
- multi objective optimization problems
- multi objective evolutionary algorithms
- fitness function
- multiple objectives
- bi objective
- solution quality
- genetic programming
- computational intelligence
- branch and bound algorithm
- np hard
- simulated annealing
- pareto frontier
- computational complexity
- genetic algorithm ga