However, a steady-state assumption is generally invalid in evolution and ecology because although the population size may be stable, individual performances are definitely variable, and, in fact, in biology, steady states are never permanent. Such an analytic approach is only possible to problems of low or intermediate complexity. Adaptation models were developed for more complex situations when the optimal assumption will be invalid and when solutions cannot be found by conventional methods. The behavioural strategies that a given organism uses are those that have evolved and have been maintained in the population through long periods of natural selection. Evolution occurs continually and survivors become steadily adapted to new situations.
Survivors exist because their ancestors executed their inherited adaptations.
Genetic algorithms are inspired from the principle of evolution by natural selection in order to generate the optimal solution to a given problem. They have also played a central role in the development of artificial life. A genetic algorithm may be considered as a wheel where each cycle represents a generation. In GA, a generation wheel is defined according to the features described below in order to address a particular problem. While all possible solutions may then be examined, this may be impossibly time consuming.