Effect of local search on the performance of cellular multiobjective genetic algorithms for designing fuzzy rule-based classification systems.
Tadahiko MurataHiroyuki NozawaYasuhiro TsujimuraMitsuo GenHisao IshibuchiPublished in: IEEE Congress on Evolutionary Computation (2002)
Keyphrases
- classification systems
- multi objective
- genetic algorithm
- evolutionary algorithm
- optimization algorithm
- multi objective optimization
- particle swarm optimization
- multiobjective optimization
- simulated annealing
- multiple objectives
- cellular automata
- tabu search
- global search
- nsga ii
- evolutionary computation
- uniform design
- simulated annealing and tabu search
- fitness function
- genetic programming
- selection operator
- fuzzy logic
- neural network
- memetic algorithm
- job shop scheduling problem
- artificial neural networks
- multiobjective genetic algorithm
- hierarchical text classification
- search algorithm
- conflicting objectives
- genetic operators
- metaheuristic
- combinatorial optimization
- fuzzy rules
- objective function
- genetic algorithm ga
- bi objective
- population size
- artificial bee colony
- search heuristics
- differential evolution
- hybrid ga
- evolutionary search
- multiobjective evolutionary algorithms
- multiobjective evolutionary algorithm
- text classification tasks
- search space
- multiple classifier systems
- active learning
- trade off
- pareto optimal