Using a directed mutation can improve the efficiency of processing many optimization problems. The first mutation operators of this kind proposed by Hildebrand [1], however, suffer...
Genetic algorithms are adaptive methods based on natural evolution that may be used for search and optimization problems. They process a population of search space solutions with t...
Abstract–A new evolutionary programming algorithm (NEP) using the non-uniform mutation operator instead of Gaussian or Cauchy mutation operators is proposed. NEP has the merits o...
This paper presents a particle swarm optimizer for solving constrained optimization problems which adopts a very small population size (five particles). The proposed approach uses...
Juan Carlos Fuentes Cabrera, Carlos A. Coello Coel...
Evolutionary and genetic algorithms (EAs and GAs) are quite successful randomized function optimizers. This success is mainly based on the interaction of different operators like ...