Optimum geometrical pattern and design of real-size diagrid structures using accelerated fuzzy-genetic algorithm with bilinear membership function

Diagrids are the efficient systems of tube structures for tall buildings. One of the design considerations for these structures is the geometrical pattern of the system. In this paper, a new method of fuzzy genetic algorithm based on bilinear membership functions is proposed with an improved crossover operator and penalty function. The method is applied on tall buildings with a diagrid system to find the optimum geometrical patterns and the overall structural weight. Various three-dimensional diagrid structures with 24, 36, 42, 56, and 60 stories and different slenderness ratios are analyzed under gravity and wind load. Then the effects of variation in the number of bays (4, 6, and 8) are investigated and compared with each other. The results show that by increasing the dimension of the structure, the structural weight is reduced up to 33% in some cases. However, the obtained angle of the diagrid members (range of 63 to 79 degrees) is increased by increasing the number of stories and the height of the structure. The optimum weight and geometrical pattern of the models is obtained and a formulation is extracted from the results regarding the optimum angle of a diagrid system. Considering GA, results show the merit of the accelerated fuzzy-genetic algorithm regarding the convergence and the avoidance of being trapped in local minimum. (C) 2021 Elsevier B.V. All rights reserved.

Automated summary

A new method of fuzzy genetic algorithm based on bilinear membership functions is proposed for finding the optimal geometrical patterns and overall structural weight of tall buildings with a diagrid system. Results show that increasing the dimension of the structure can reduce structural weight, while also increasing the angle of the diagrid members. The accelerated fuzzy-genetic algorithm proves to be advantageous in terms of convergence and avoiding local minimum traps.