A HYBRID GENETIC ALGORITHM AND OPTIMALITY CRITERIA METHOD FOR OPTIMUM DESIGN OF RC TALL BUILDINGS UNDER MULTI-LOAD CASES

摘要

This paper proposes a hybrid heuristic and criteria-based method of optimum design that combines the advantages of both the genetic algorithm (GA) and the rigorously derived optimality criteria (OC) for structural optimum design of reinforced concrete tall buildings under multi-load cases based on the current Chinese design codes. The entire optimum design procedure is divided into two parts: strength optimum design and stiffness optimum design, which are performed by the GA and the OC method, respectively. The optimum reinforcement detailing, which satisfies the strength, serviceability, ductility and other constraints related to the user-specified rules and regulations in design codes, is achieved by constructing the data sets containing different available reinforcement bar diameter in a pre-specified pattern. An adaptive feasible region technique is developed to improve the efficiency of GA. Finally, a practical frame-shear-wall structure (30-storey) is optimized to illustrate the effectiveness and practicality of the proposed optimum design method.