Genetic Algorithms (GAs), are a search and optimization method inspired in the way nature works with living entities, using evolutionary-based operators. These operators exchange genetic information through different generations until an ending condition, typically the desired solution, is found. In this entry, the formalism of why GAs work is described as proposed by Holland in the middle seventies and later by Goldberg. To do so, we first need to introduce some key concepts, assuming the classical ternary representation {0, 1, *}, where * is the don't care symbol.

A fundamental concept in GA theory is the one of schema. A schema is a particular subset among the set of all possible binary strings described by a template composed of the ternary alphabet {0, 1, *}. For instance, the schema 01**1 corresponds to the set of strings of length five (that is, strings composed of five symbols from the ternary alphabet) with a 0 in the first position, an 1 in the second position and an 1 in…

A fundamental concept in GA theory is the one of schema. A schema is a particular subset among the set of all possible binary strings described by a template composed of the ternary alphabet {0, 1, *}. For instance, the schema 01**1 corresponds to the set of strings of length five (that is, strings composed of five symbols from the ternary alphabet) with a 0 in the first position, an 1 in the second position and an 1 in…