Improving approximate-TMR using multi-objective optimization genetic algorithm.
Iuri Albandes Cunha GomesAlejandro Serrano-CasesAntonio J. Sanchez-ClementeMayler G. A. MartinsAntonio Martínez-ÁlvarezSergio Cuenca-AsensiFernanda Lima KastensmidtPublished in: LATS (2018)
Keyphrases
- multi objective optimization
- genetic algorithm
- multi objective
- evolutionary algorithm
- crossover and mutation
- differential evolution
- nsga ii
- pareto optimal
- multiple objectives
- pareto optimal set
- multi objective optimization problems
- multiobjective optimization
- evolutionary computation
- bi objective
- optimization algorithm
- fuzzy logic
- hybrid evolutionary algorithm
- evolutionary strategy
- multi objective evolutionary algorithms
- fitness function
- multi objective genetic algorithm
- multi objective genetic algorithms
- pareto frontier
- genetic search
- solving multi objective optimization problems
- pareto optimal solutions
- genetic operators
- mutation operator
- genetic algorithm ga
- cost function
- artificial neural networks
- objective function