This is an inherent contradiction of elastic timber gridshells, which generally require an iterative sizing process. Consequently, it is necessary to have some procedure to generate the grid and evaluate the bending stresses from the preliminary design stages to ensure appropriate values. This is one of the main challenges in the design of elastic timber gridshells. In traditional elastic timber gridshells, two types of mesh have been used to generate the grid: the geodesic meshes in the ribbed shells of [PERSON] [11], and the constant-sided quadrangular meshes in the gridshells of [PERSON] [2]. Geodesic meshes have the advantage that laths are subjected to bending only about their weak axis, but the disadvantage that the distance between nodes is variable on free-form surfaces, which can cause the grid to have an irregular appearance. In contrast, quadrangular grids keep a constant distance between nodes, offering a more regular pattern for any surface, but have the disadvantage that the laths are subjected to bending about both weak and strong axes. In elastic timber gridshells for building construction, the general problem to be solved is usually to determine the grid geometry on an imposed architectural surface, which has been approached in different ways. In recent years, several research studies have focused on the dynamic relaxation method with kinetic damping for gridshell form-finding thanks to its suitability for non-linear systems with large displacements [12; 13; 14; 15]. This approach determines the deformed grid geometry on an imposed architectural surface by relaxation [16; 17] and can be applied for both geodesic and quadrangular meshes. Another very different approach lies in the use of geometric methods rather than mechanical simulations. In this regard, the Compass Method (CM) described in [2] has been applied for the generation of quadrangular meshes in the design of gridshells made of timber [18] and other materials [19]. However, this approach has the drawback of requiring the definition of two random initial (master) curves over the surface, whose position and shape have a major impact on the resulting mesh. In addition, the CM shows dimensional accuracy errors when the target surface has high local curvature. This drawback can be overcome by applying the Improved Compass Method (ICM) [20] but doing so requires a significant increase in computational time. In elastic gridshells, the stresses due to the construction process are the most important loads [9; 10], so minimising the initial stresses due to bending for a given cross-section is always a desirable objective that depends exclusively on the material and the grid geometry. Genetic algorithms (GAs) have been developed especially in the last two decades [21] and have been applied successfully to solve structural optimisation problems. The development of such optimisation algorithms is analogous to evolutionary theory, as the individuals generated in the solution space after each generation evolve in a kind of natural selection, and have been widely described in the last decades [22]. This natural selection is performed by measuring how fit each individual in a population is by testing how high its score is against a predefined fitness function (FF). The fitter the individual is, the more likely it is to pass on its genes to its offspring for the next generation. The optimal solution is found after a recursive evolution of a population of individuals or chromosomes (solution vectors or parameters in the solution space) until the optimality criterion is reached [23] or no improvement is achieved. In this evolutionary process, stronger or fitter individuals (higher score value from the FF) have more chances to pass their genes (variable parameters or components of a solution vector) to the next generation of individuals by means of reproduction, combining the parents' genes through gene crossover. During evolution, mutation may occur, introducing random diversity in the population and preventing local optima convergence [24].