A new stochastic global algorithm for critical load optimization of dome trusses A new stochastic global algorithm for critical load optimization

• Published in: Optimization and engineering Vol. 26; no. 2; pp. 1143 - 1202
• Main Authors: Dao, Ngoc Tien, Van Tran Thi, Thuy, Cuong-Le, Thanh
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.06.2025
• Subjects: Control; Engineering; Environmental Management; Financial Engineering; Mathematics; Mathematics and Statistics; Operations Research/Decision Theory; Optimization; Research Article; Systems Theory; Global optimization; Load limit points; Dome truss; Optimization problem; Global random search; Limit load
• ISSN: 1389-4420; 1573-2924
• DOI: 10.1007/s11081-024-09932-1

This article introduces a novel algorithm based on the random search technique, namely the p-Stochastic Global Optimization Algorithm (p-SGOA). After each iteration, the search space is gradually narrowed exponentially around the global optimal point, leading to a faster convergence speed. p-SGOA also randomly selects samples p times to find the optimal global solution. The reliability and efficiency of p-SGOA were demonstrated through the application of twenty-three well-known test functions, comparing it with other optimization algorithms. The problem of optimizing the critical load for a single-layer dome truss with the design variable as ‘small change of truss element length’ is also proposed in this study. The p-SGOA algorithm was applied to solve the problem of the critical load optimization of the truss. From the optimization examples of the dome truss, it is shown that only a small change in truss element length can significantly increase the value of the critical load. This conclusion has practical significance, as it allows an increase in the overall stability of the truss through ‘small changes in the length of the truss elements’ without affecting the weight or the original designed shape of the truss. Source codes of p-SGOA are publicly available at   https://ceats.ou.edu.vn/us/p-stochastic-global-optimization-algorithm.html .