An application of genetic algorithms (GAs) to the system optimization of failure, constitutive modeling, and strengths of concrete and other geological materials is presented. GA is a relatively new, general purpose, optimization algorithm that applies the rules of natural genetics to explore a given search space. Knowledge of the basic constitutive properties of concrete and other geological materials is needed to analyze service load characteristics, design, and evaluate strengths. GA can be used to evaluate parameters of a concrete constitutive modeling, which is based on the theory of plasticity. All the parameters are constants for an ultimate (failure) yielding condition. GA also can be used to evaluate parameters of tensile and compressive strengths for frictional materials such as igneous, sedimentary, and metamorphic rocks; ceramics; mortar; polymer concrete; porous limestone; river gravel; dense limestone; and cemented soils. Such parameters are constants for failure (strengths) conditions. Numerical results indicate that GA is capable of optimizing the system parameters quickly and accurately. Resulting parameter values agree well with previous studies.