Darwin's theory of evolution says that the more suitable an individual is to his environment, the more likely that individual is to reproduce. Conversely, the less suited an individual is to his environment the less likely he is to reproduce. Consequently, by the laws of heredity, the fitness of the subsequent generation, as a whole, should be greater than the last.  The Truckin' project attempts to use these theories and laws to prove that a program can also evolve. Using evolutionary programming and object oriented techniques, Truckin' simulates a world in which trucks buy and sell commodities competing for the best deals. The most successful of these trucks are allowed to 'reproduce' and compete in the next generation. Over a period of time the truck population should converge to an overall fitter population.  In this thesis the basics of genetic algorithms are explained and then the Truckin' project is described in detail. Finally the results and current status of the project are outlined.