This work investigates the solution to inverse problems in heat transfer using genetic algorithms. Genetic algorithms are robust, stochastic search techniques which also admit the ability to search highly nonlinear problems. In this work, computational techniques are developed for the simultaneous inverse identification the internal heat generation and the thermal diffusivity of early age concrete as functions of time, as well as constant convective coefficients. Through the use of several numerical examples it is shown that this methodology yields accurate results for the inverse heat transfer problem in finding several unknown conditions simultaneously.