A multi-stage descent algorithm for discrete and continuous optimization applied to truss structures optimal design

被引:3
|
作者
Sellami, Mohamed [1 ,2 ]
机构
[1] Univ Gabes, Natl Engn Sch Gabes, Mech Modeling Energy & Mat M2EM, Res Unit, Gabes 6029, Tunisia
[2] Univ Gabes, Natl Engn Sch Gabes, Dept Civil Engn, Gabes 6029, Tunisia
关键词
FILLED FUNCTION-METHOD; PARTICLE SWARM OPTIMIZATION; SIZING OPTIMIZATION; GENETIC ALGORITHM; SEARCH; SIZE;
D O I
10.1007/s00707-023-03630-2
中图分类号
O3 [力学];
学科分类号
08 ; 0801 ;
摘要
In this paper the step by step descent algorithm is extended to continuous optimization problems and applied to the optimal sizing of truss structures. The step by step descent method, recently developed, was applied to the discrete optimization of rigid structures. To solve continuous problems, a multi-stage optimization algorithm is proposed, which involves implementing the step by step descent method in multiple stages. In each stage, the continuous areas of the variables are progressively divided into a finite number of points. The algorithm is based on the search for the steepest gradient descent direction that minimizes the cost function and employs a wise heuristic approach to bypassing local optima. To evaluate the algorithm's performance, a study was carried out on ten mathematical and four truss optimization problems. For unconstrained mathematical problems, the algorithm demonstrates quick converges to optimum solution from any starting point. For truss structures, the starting design point is selected based on structural knowledge to enhance convergence speed. The obtained results surpass those achieved by other state-of-the-art optimization algorithms, affirming the efficiency, robustness and the promptness of the proposed method.
引用
收藏
页码:4837 / 4857
页数:21
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