Over the past few decades, buildings energy consumption has risen seriously due to the growth of population and to the increase demand of comfort in indoor environment. Thus, the use of low thermal conductivities building materials and the development of powerful techniques to determine their thermal properties are receiving greater attention. To this end, lightweight mortar samples made with different percentage of polystyrene beads and wood shavings have been prepared and thermally characterized. To determine the thermal properties of these lightened mortar samples, an inverse problem based on a hybrid algorithm combining a genetic algorithm and the Nelder Mead simplex algorithm has been implemented. The experimental bench using the boxes method has been used in transitory state. The implemented hybrid algorithm is used to minimize an objective function which represents the gap between a measured temperature and a calculated one. The obtained results demonstrate that the thermal conductivities and the densities of the elaborated samples have been improved until 71% and until 36%, respectively. Thus, energy consumption in buildings is expected to decrease. In addition the replacement of a percentage of cement by wood shavings and polystyrene beads leads to a reduction of the total produced energy and in CO2 emission. Furthermore, results show that the implemented hybrid algorithm has the ability to correlated parameters and the efficiency to combine convergence speed and accuracy of results. (C) 2016 Elsevier B.V. All rights reserved.