Application of evolutionary global optimization techniques in the design of RC water tanks

This paper presents evolutionary-based optimization procedures for designing conical reinforced concrete water tanks. The material cost of the tank that includes concrete, reinforcement, and formwork required for walls and floor was chosen as the objective function in the nonlinear optimization problem formulation. The wall thicknesses (at the bottom and at the top), base thickness, depth of water tank, and wall inclination were considered as design variables. advanced optimization techniques to solve the nonlinear constrained structural optimization problems were investigated. These methods are: (1) Shuffled Complex Evolution (SCE), (2) Simulated Annealing (SA) and Genetic Algorithm (GA). Several tests were performed to illustrate the robustness of these techniques and results were encouraging for SCE Method. The SCE method proved to be superior to the SA and GA methods in obtaining the best discovered solutions. The paper concludes that the robust search capability of SCE algorithm technique is well suited for solving the structural problem in hand.