Optimum design of 3D reinforced concrete frames using DMPSO algorithm

Evolutionary optimization algorithms are widely used for solving optimization problems. However, in the realm of real-world structures finding the optimum design would be difficult and time-consuming due to large number of design variables, enormous size of the search space, and availability of numerous constraints. As a result, holistic optimization approaches that consider architectural and other practical requirements in addition to required code provisions are rather limited in real-world structures. This paper presents an innovative algorithm combining multi-criterion decision-making (DM) and Particle Swarm Optimization (PSO), which is called DMPSO, for accelerating convergence toward optimum solution in 3D reinforced concrete (RC) frames. All practical requirements are considered for obtaining directly constructible designs without any further modifications. The effectiveness of the proposed algorithm is illustrated in optimization of 3D RC frames subjected to lateral seismic forces according to ASCE 7 requirements. The results confirm the ability of the proposed DMPSO algorithm to efficiently find optimal solutions for 3D RC optimization problems.