Stopping criteria in evolutionary algorithms for multi-objective performance optimization of integrated inductors.
Francisco V. FernándezJuan Esteban-MullerElisenda RocaRafael Castro-LópezPublished in: IEEE Congress on Evolutionary Computation (2010)
Keyphrases
- multi objective
- evolutionary algorithm
- optimization algorithm
- stopping criteria
- optimization problems
- multi objective optimization
- multiple objectives
- optimization method
- evolution strategy
- multiobjective optimization
- evolutionary optimization
- evolutionary computation
- conflicting objectives
- particle swarm
- evolutionary strategy
- optimum design
- differential evolution
- multi objective optimization problems
- fitness function
- genetic programming
- particle swarm optimization
- genetic algorithm
- simulated annealing
- multiobjective evolutionary algorithms
- estimation of distribution algorithms
- differential evolution algorithm
- global optimization
- multi objective evolutionary algorithms
- engineering design problems
- evolutionary search
- nsga ii
- optimization methods
- metaheuristic
- clustering algorithm
- bi objective
- genetic operators
- evolutionary process
- test problems
- combinatorial optimization
- multiobjective evolutionary algorithm
- multidisciplinary design optimization
- pareto optimal
- neural network
- knapsack problem
- tabu search
- benchmark problems
- multi objective problems