Crossover (evolutionary algorithm)

Crossover in evolutionary algorithms and evolutionary computation, also called recombination, is a genetic operator used to combine the genetic information...

genetic algorithm (GA) is a metaheuristic inspired by the process of natural selection that belongs to the larger class of evolutionary algorithms (EA)....

Evolutionary algorithms (EA) reproduce essential elements of biological evolution in a computer algorithm in order to solve "difficult" problems, at least...

Evolutionary programming is an evolutionary algorithm, where a share of new population is created by mutation of previous population without crossover...

Cultural algorithms (CA) are a branch of evolutionary computation where there is a knowledge component that is called the belief space in addition to the...

diversity of the chromosomes of a population of an evolutionary algorithm (EA), including genetic algorithms in particular. It is analogous to biological mutation...

Evolutionary computation from computer science is a family of algorithms for global optimization inspired by biological evolution, and the subfield of...

The Fly Algorithm is a computational method within the field of evolutionary algorithms, designed for direct exploration of 3D spaces in applications...

operations research, a memetic algorithm (MA) is an extension of an evolutionary algorithm (EA) that aims to accelerate the evolutionary search for the optimum...

solutions (crossover) and select between solutions (selection). The classic representatives of evolutionary algorithms include genetic algorithms, evolution...