A novel strategy for the crossarm length optimization of PSSCs based on multi-dimensional global optimization algorithms

• Published in: Engineering structures Vol. 238; p. 112238
• Main Authors: Li, Pengcheng, Wang, Hao
• Format: Journal Article
• Language: English
• Published: Kidlington Elsevier Ltd 01.07.2021; Elsevier BV
• Subjects: Algorithms; Bearing strength; Buckling load; Carrying capacity; Compression; Crossarm length; Design optimization; Genetic algorithms; Global optimization; Load carrying capacity; Multi-population genetic algorithm; Optimization algorithm; Optimization algorithms; Population genetics; PSSC; Steel columns; Buckling load; Optimization algorithm; Multi-population genetic algorithm; PSSC; Crossarm length
• ISSN: 0141-0296; 1873-7323
• DOI: 10.1016/j.engstruct.2021.112238

•A novel optimization method of determining the optimal crossarm length of PSSC.•The method overcomes the drawbacks in the gradient-based optimization algorithm.•A comparison for the optimal PSSCs with different kinds of variables was performed. Prestressed stayed steel columns (PSSCs) offer a lightweight alternative for the design of slender compression columns. The stability of compression columns can be significantly enhanced by introducing crossarms. Previous research on this subject has primarily focused on load-carrying capacity estimation or analyses of the influencing factors of PSSCs. Thus, investigations of the design optimization of PSSCs remain scant. This work proposes a novel strategy for crossarm length optimization of PSSCs based on multi-dimensional global optimization algorithms. A multi-population genetic algorithm is introduced in the optimization process. The proposed optimization algorithm was demonstrated to be efficient and accurate in terms of determining the optimal crossarm length of PSSCs.