To simulate the process of natural selection in a computer, we
need to define a representation of an individual.
For example, say we want to find the optimal quantity of the
three major ingredients in a recipe (say, sugar, wine, and
sesame oil). We can use the alphabet {1, 2, 3 ..., 9}
denoting the number of ounces of each ingredient. Some possible solutions
are 1-1-1, 2-1-4, and 3-3-1. These could all be individuals in the
same population, together with other possible solutions.
Individuals in the population can be represented in many different ways,
e.g. arrays trees or lists.
At each point during the search process we maintain a "generation"
of "individuals." Each individual is a data structure representing
the "genetic structure" of a possible solution or hypothesis.
Like a chromosome, the genetic structure of an individual is
described using a fixed, finite alphabet. In GAs, the
alphabet {0, 1} is usually used. This string is
interpreted as a solution to the problem we are trying to solve.
As another example, the traveling salesperson problem is the problem of
finding the optimal path to traverse, say, 10 cities. The
salesperson may start in any city. A solution
is a permutation of the 10 cities: 1-4-2-3-6-7-9-8-5-10. 