Optimum structural design of spatial steel frames via biogeography-based optimization

被引:26
|
作者
Carbas, Serdar [1 ]
机构
[1] Karamanoglu Mehmetbey Univ, Dept Civil Engn, Karaman, Turkey
来源
NEURAL COMPUTING & APPLICATIONS | 2017年 / 28卷 / 06期
关键词
Structural design optimization; Spatial steel frames; Metaheuristic techniques; Biogeography-based optimization; LRFD-AISC; DISCRETE SIZING OPTIMIZATION; BAT-INSPIRED ALGORITHM; BIG CRUNCH ALGORITHM; SEARCH; TRUSSES;
D O I
10.1007/s00521-015-2167-6
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Metaheuristic algorithms have provided an efficient tool for designers by which discrete optimum design of real-size steel space frames under design code requirements can be obtained. In this study, the optimum sizing design of steel space frames is formulated according to provisions of Load and Resistance Factor Design-American Institute of Steel Construction. The weight of the steel frame is taken as objective function. The design algorithm selects the appropriate W sections for members of the steel frame such that the frame weight is the minimum and design code limitations are satisfied. The biogeography-based optimization algorithm is utilized to find out the optimum solution of the discrete programming problem. This algorithm is one of the recent additions to metaheuristic techniques which are based on theory of island biogeography where each habitat is assumed to be potential solution for the design problem. The performance of the biogeography-based optimization algorithm is compared with other recent metaheuristic algorithms such as adaptive firefly algorithm, teaching and learning-based optimization, artificial bee colony optimization, dynamic harmony search algorithm, and ant colony algorithm. It is shown that biogeography-based optimization algorithm outperforms other metaheuristic techniques in the design examples considered.
引用
收藏
页码:1525 / 1539
页数:15
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