Evolutionary algorithms (EA) reproduce essential elements of
biological evolution in a computer algorithm in order to solve "difficult"
problems, at least approximately, for which no exact or satisfactory solution
methods are known. They are metaheuristics and population-based bio-inspired
algorithms and evolutionary computation, which itself are part of the field of
computational intelligence. The mechanisms of biological evolution that an EA
mainly imitates are reproduction, mutation, recombination and selection.
Candidate solutions to the optimization problem play the role of individuals
in a population, and the fitness function determines the quality of the
solutions (see also loss function).