This chapter describes the Evolutionary Algorithms that indicates a range of systems of the problems’
resolution based on the use of computer, similar to the evolutionary processes. They include, Genetic
Algorithms, Evolutionary Programming, Evolutionary Strategies, Classifying Systems, Genetic Programming,
and Genetic Doping Algorithm (GenD), an evolutionary algorithm, conceived by Buscema in 1998, at
the Semeion Research Centre in Rome, where it is still successfully used and has been further developed.
Unlike classic genetic algorithms, the GenD system maintains an inner instability during evolution, presenting
a continuous evolution and a natural increase in biodiversity during the progress of the algorithm. The
theory, which leads to defining the GenD system is outlined. Specific characteristics of GenD, such as the
definition of a species-health aware evolutionary law, the use of genetic operators and the adoption of a structured
organisation of individuals (tribes), are described. In order to measure GenD capabilities, we investigated
also different problems, such as that known as the travelling sales person problem, which belongs to the
class of full NP problems.
Keywords: Genetic Algorithms, Evolutionary Algorithms, Natural Evolution, Biodiversity.
