ABSTRACT
An evolutionary algorithm (EA) belongs to the field of computational intelligence. It is a population-based algorithm inspired by biological evolution process. It is a step-by-step process that involves reproduction, mutation, recombination, and selection. The possible solutions to the optimization problem act as individuals in a population, and the fitness function evaluates the quality of these solutions. EAs often perform well approximating solutions to all types of problems. This chapter discusses general implementation of different EAs along with their characteristics. ECs have the capability of solving several combinatorial optimization problems and continuous optimization problems through natural evolutionary mechanism. This chapter also highlights genetic algorithm and its variants. It also discusses genetic programming and languages used for genetic programming.
