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...
In this paper we propose an agent-based model of evolutionary algorithms (EAs) which extends seamlessly from concurrent single-host to distributed multi-host installations. Since ...
Background: The development, in the last decade, of stochastic heuristics implemented in robust application softwares has made large phylogeny inference a key step in most compara...
The fast messy genetic algorithm (fmGA) belongs to a class of algorithms inspired by the principles of evolution, known appropriately as "evolutionary algorithms" (EAs)....
Laurence D. Merkle, George H. Gates Jr., Gary B. L...
In this paper, a novel approach for designing chromosome has been proposed to improve the effectiveness, which called multistage operation-based genetic algorithm (moGA). The obje...