Fire characteristics can be analyzed more realistically by using more accurate material properties related to the tire dynamics and one way to acquire these fire properties is to use one of the inverse property estimation techniques. In this study an optimization algorithm which is frequently applied for the inverse heat transfer problems is selected to demonstrate the procedure of obtaining fire properties of a solid charring material with relatively simple chemical structure. Thermal decomposition is occurred at the surface of the test plate by receiving the radiative energy from external heat sources and in this process the heat transfer through the test plate can be simplified by an unsteady one dimensional problem. The input parameters for the analyses are the surface temperature and mass loss rate of the char plate which are determined from the actual experiment of from the unsteady one-dimensional analysis with a given set of eight properties. The performance of hybrid genetic algorithm (HGA) is compare with a basic genetic algorithm (GA) in order to examine its performance. This comparison is carried out for the inverse property problem of estimating the fire properties related to the reaction pyrolysis of some relatively simple materials; redwood and red oak. Results show that the hybrid genetic algorithm has better performance in estimating the eight pyrolysis properties than the genetic algorithm.