Abstract: Gas lift is one of a number of processes used to artificially lift oil or water from wells where there is insufficient reservoir pressure to produce the well. The process involves injecting gas through the tubing-casing annulus. Injected gas aerates the fluid to reduce its density; the formation pressure is then able to lift the oil column and forces the fluid out of the wellbore. Gas may be injected continuously or intermittently, depending on the producing characteristics of the well and the arrangement of the gas-lift equipment. To enhance the financial revenues this operation has usually always been a subject for optimization to reach the most rewarding design before its operational establishment. Evolutionary approaches have recently been successfully applied to almost every aspect of engineering problems. This study reviews the general facts and ideas related to the gas lift and its optimization and further focus on the application and evaluation of genetic programming for such a purpose. It has been concluded that genetic programming is fully capable in aiding faster gas lift optimizations while is also stable and applicable to a very broad range of operating conditions. The merits and draw backs are finally compared with the neural network approach.