It is possible to see various applications of mathematical optimization in civil engineering (structural design, reconstruction of transportation networks etc.) Initially, deterministic approaches have been introduced to solve these problems. But despite their complexity, these approaches are insufficient to comprehend the probabilistic nature of said problems and thus provide only suboptimal solutions. Hence the effort comes to reconsider these deterministic approaches and deal with uncertainties involved in said problems in less straightforward way. The goal of the paper is to present the algorithm for stochastic optimization of design of steel-reinforced concrete cross-section. This algorithm is based on internal cycle of deterministic optimization using reduced gradient method and external cycle of stochastic optimization using regression analysis. Firstly, the deterministic problem is introduced and described. It is followed by the description of uncertainties, which are involved in the process, and stochastic reformulation of the problem. Then the algorithm itself is introduced and the paper ends with presentation of the results of performed calculations.