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Response Surface Methodology is a combination of experimental designs and statistical techniques for empirical model building and optimisation which has been applied to a wide range of fields. Recently, genetic algorithms have been developed to solve optimisation in stages where response surface models require maximization or minimization. GA’s are evolutionary algorithms which have been found to be very useful at interfacing with response surfaces, as recent results in scientific literature testify. This paper shows how Genetic Algorithms can be used when RSM is applied and an optimisation process is required. A review of the recent scientific literature has been carried out. Some of these references are presented with the purpose of showing the use of Genetic Algorithms in practical applications of RSM.