Evolutionary Algorithms (EAs) are inspired by the Darwin's theory of natural selection and survival of the fittest individuals. EAs are using multiple potential solutions (a population) in order to solve the required problem. A potential solution also called individual or chromosome, is a point in the search space. A potential solution is not quite a perfect solution but it can be during the search process.

Initially all solutions are randomly generated. Some of them are better and others are worse. The search process is continued by using some biologically inspired procedures such as: Selection, Crossover and Mutation. New and hopefully better individuals are obtained by using these procedures.

By Selection some of the best individuals are selected for later use.

By Crossover, two or more individuals exchange information between them. Exchanging information usually means exchanging parts of the individuals. For instance if the individuals are arrays we can cross them over by taking a crossover point and exchanging the parts after that point.