Evolutionary computation is a family of optimization methods and research approaches inspired by natural evolution. These methods use populations of candidate solutions and stochastic search processes to solve difficult optimization and adaptation problems.
A family of algorithms for global optimization inspired by biological evolution, and the subfield of artificial intelligence and soft computing studying these algorithms. In technical terms, they are a family of population-based trial and error problem solvers with a metaheuristic or stochastic optimization character.