# Chromosome (genetic algorithm)

The design of the chromosome and its parameters is by necessity specific to the problem to be solved. To give a trivial example, suppose the problem is to find the integer value of $x$ between 0 and 255 that provides the maximal result for $f(x) = x^2$. (This isn't the type of problem that is normally solved by a genetic algorithm, since it can be trivially solved using numeric methods. It is only used to serve as a simple example.) Our possible solutions are the integers from 0 to 255, which can all be represented as 8-digit binary strings. Thus, we might use an 8-digit binary string as our chromosome. If a given chromosome in the population represents the value 155, its chromosome would be 10011011.
A more realistic problem we might wish to solve is the travelling salesman problem. In this problem, we seek an ordered list of cities that results in the shortest trip for the salesman to travel. Suppose there are six cities, which we'll call A, B, C, D, E, and F. A good design for our chromosome might be the ordered list we want to try. An example chromosome we might encounter in the population might be DFABEC.