A multi-objective niching co-evolutionary algorithm (MNCA) for identifying diverse sets of non-dominated solutions.
Emily M. ZechmanMarcio H. GiacomoniM. Ehsan ShafieePublished in: GECCO (Companion) (2011)
Keyphrases
- evolutionary algorithm
- multi objective
- multi objective optimization problems
- multi objective optimization
- conflicting objectives
- multiple objectives
- genetic operators
- evolutionary computation
- optimization algorithm
- multi objective evolutionary algorithms
- engineering design problems
- pareto optimal solutions
- bi objective
- optimization problems
- pareto optimal
- multiobjective optimization
- evolutionary search
- particle swarm optimization
- nsga ii
- multi objective problems
- fitness function
- genetic programming
- differential evolution
- initial population
- simulated annealing
- pareto optimal set
- genetic algorithm
- pareto frontier
- function optimization
- simulated annealing and tabu search
- evolutionary process
- multi objective genetic algorithms
- single objective optimization
- evolution strategy
- real world
- optimal solution
- metaheuristic
- solution quality
- test functions
- mutation operator
- wide variety
- evolutionary strategy
- particle swarm
- particle swarm optimizer
- evolutionary optimization
- genetic algorithm ga
- trade off
- lower bound
- multi objective evolutionary
- multi criteria
- estimation of distribution algorithms