The genetic possibilities of a single creature are rather limited. Similarly, in order to solve discrete problems, it will be necessary to work with a population of solutions. These solutions will be encoded in some manner. Later, we will discuss what features an encoding should have. For now, let us encode our solution as 0-1 strings.
Genetic algorithms require very little information about a problem.
Let us assume that we have a black box that can take a solution string and return a function value. Let us work with a particular black box, whose workings can be a mystery for the moment. One nice feature about genetic algorithms is that we explore a large number of points simultaneously. This permits us to escape poor local optima quickly. This sample is called the population .