Hybridization of NSGA-II with greedy re-assignment for variation tolerant logic mapping on nano-scale crossbar architectures.
Fugui ZhongBo YuanBin LiPublished in: GECCO (Companion) (2014)
Keyphrases
- nsga ii
- nano scale
- multi objective
- multi objective optimization
- test problems
- evolutionary algorithm
- pareto optimal
- multiobjective optimization
- multiobjective evolutionary algorithm
- optimization problems
- evolutionary multiobjective
- optimization algorithm
- evolutionary multiobjective optimization
- multi objective differential evolution
- multi objective evolutionary algorithms
- knapsack problem
- multi objective optimization problems
- genetic algorithm
- greedy algorithm
- constrained multi objective optimization problems
- optimal solution
- multi objective optimisation
- uniform design
- differential evolution
- test functions
- dynamic programming
- fitness function
- mutation operator
- bi objective
- crossover operator
- pareto optimal solutions
- search algorithm
- feature selection
- multiple objectives
- particle swarm optimization
- multi objective genetic algorithm
- pareto optimal set
- pareto frontier
- strength pareto evolutionary algorithm
- multi agent systems
- pareto dominance
- neural network
- branch and bound algorithm
- multi objective problems
- lower bound
- search space
- upper bound
- particle swarm optimization algorithm