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作者机构:Univ Zanjan Fac Engn Dept Civil Engn Zanjan Iran
出 版 物:《MECHANICS BASED DESIGN OF STRUCTURES AND MACHINES》 (基于设计的结构力学与机械力学)
年 卷 期:2020年第48卷第6期
页 面:697-723页
核心收录:
学科分类:08[工学] 0801[工学-力学(可授工学、理学学位)] 080102[工学-固体力学]
主 题:Improved differential evolution discrete optimization metaheuristic algorithms steel frames structural optimization robust algorithm
摘 要:New metaheuristic algorithms have been shown to be robust and effective for engineering optimization problems. Differential Evolution (DE), which is one of the most famous optimization approaches developed for optimal design problems with continuous design variables, is, in fact, inappropriate for constrained problems containing discrete design variables. In this article, an improved constrained differential evolution (iCDE) algorithm is proposed for optimization of steel frames with discrete design variables, followed by comprehensive testing of iCDE to validate the results. In order to make iCDE more efficient, two novel mutation approaches are proposed and tested. Three benchmark structural optimization problems are evaluated by the algorithm and compared against those reported in the literature obtained by GA, ACO, IACO, ICA, HS, and SBO. The total weight of the frame is considered as the objective function and the cross sections of the elements are taken as design variables. Constraints are based on the stress and displacement requirements conforming to the AISC-LRFD specifications. Moreover, to demonstrate the robustness of the algorithm, eight benchmark test functions of CEC-2017 are evaluated. The results show that the iCDE algorithm is computationally efficient and robust enough to find the global optima. Communicated by Janos Logo.