When hypermutations and ageing enable artificial immune systems to outperform evolutionary algorithms.
Dogan CorusPietro S. OlivetoDonya YazdaniPublished in: Theor. Comput. Sci. (2020)
Keyphrases
- evolutionary algorithm
- artificial immune system
- multiobjective optimization problems
- genetic algorithm
- multi objective
- evolutionary computation
- numerical optimization
- optimization problems
- multiobjective optimization
- immune algorithm
- simulated annealing
- swarm intelligence
- artificial immune
- differential evolution
- computational intelligence
- clonal selection
- clonal selection algorithm
- fitness function
- genetic programming
- test functions
- multi objective optimization
- computational systems
- job shop scheduling problem
- evolution strategy
- genetic operators
- immune systems
- function optimization
- nsga ii
- differential evolution algorithm
- optimization algorithm
- mutation operator
- ant colony optimization
- initial population
- genetic algorithm ga
- power system
- computational intelligence methods
- decision making
- neural network