Fast Messy Genetic Algorithm을 이용한 병렬전단벽 건물의 최적설계

Abstract

Optimally designed coupled shear wall building needs to satisfy cost minimization, inter-story drift limits, code specifications on strength design and practical dimensions following building modules. Fast Messy Genetic Algorithm(fmGA) is used for discrete optimization of reinforced concrete coupled shear wall building subject to combinations of gravity loads and lateral loads. Difficulties in finding optimum sections from semi-infinite set of member sizes and reinforcement arrangements are alleviated by constructing data sets containing a finite number of sectional dimensions of coupling beams and coupled shear walls in a practical range. Optimum wall thickness and wall width, vertical and horizontal wall reinforcements, coupling beam depth, flexural reinforcements for positive and negative moments of coupling beams and shear reinforcements of coupling beam are found by the developed algorithm. It is shown that the Fast Messy Genetic Algorithm was able to reach optimum design for reinforced concrete coupled shear wall buildings. Superiority of Fast Messy Genetic Algorithm to Simple Genetic Algorithm is demonstrated by comparing convergence rate and optimized design results.