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Seyedpour, Seyed Mohammad, Pendashteh, Morteza. (1404). Shape Optimization of Truss Structures for Displacement Constraints Using a Modified Particle Swarm Optimization (MPSO) Algorithm. پژوهشنامه مدیریت اجرایی, 1(3), 1-16. doi: 10.22080/ceas.2025.29404.1017
Seyed Mohammad Seyedpour; Morteza Pendashteh. "Shape Optimization of Truss Structures for Displacement Constraints Using a Modified Particle Swarm Optimization (MPSO) Algorithm". پژوهشنامه مدیریت اجرایی, 1, 3, 1404, 1-16. doi: 10.22080/ceas.2025.29404.1017
Seyedpour, Seyed Mohammad, Pendashteh, Morteza. (1404). 'Shape Optimization of Truss Structures for Displacement Constraints Using a Modified Particle Swarm Optimization (MPSO) Algorithm', پژوهشنامه مدیریت اجرایی, 1(3), pp. 1-16. doi: 10.22080/ceas.2025.29404.1017
Seyedpour, Seyed Mohammad, Pendashteh, Morteza. Shape Optimization of Truss Structures for Displacement Constraints Using a Modified Particle Swarm Optimization (MPSO) Algorithm. پژوهشنامه مدیریت اجرایی, 1404; 1(3): 1-16. doi: 10.22080/ceas.2025.29404.1017

Shape Optimization of Truss Structures for Displacement Constraints Using a Modified Particle Swarm Optimization (MPSO) Algorithm

Civil Engineering and Applied Solutions
مقاله 1، دوره 1، شماره 3، آبان 2025، صفحه 1-16    اصل مقاله (1.85 M)
نوع مقاله: Original Article
شناسه دیجیتال (DOI): 10.22080/ceas.2025.29404.1017
نویسندگان
Seyed Mohammad Seyedpour* ؛ Morteza Pendashteh
Department of Civil Engineering, Shomal University, Amol, Iran
تاریخ دریافت: 13 خرداد 1404،  تاریخ بازنگری: 25 تیر 1404،  تاریخ پذیرش: 23 تیر 1404 
چکیده
This paper presents a modified particle swarm optimization (MPSO) algorithm for the shape optimization of truss structures under displacement constraints. The proposed MPSO employs a multi-stage strategy, where the final solution of each stage is used to reinitialize the swarm in the next stage, improving convergence accuracy. A normal-based distribution is used for swarm regeneration, promoting effective exploration around the best solution found. Design variables are the nodal coordinates of the structures, and the total weight is considered as the objective function. Design constraints include limitations on nodal displacements, and some geometric constraints are also considered. The method is evaluated using four benchmark truss examples. Results show that MPSO reduces structural weight by 7% for the 13-bar truss, 5.7% for the 25-bar truss, and 2.2% for the 52-bar truss, compared to those reported in the literature, while also maintaining or improving displacement control. In the 37-bar planar truss, the algorithm marginally outperforms the existing result by reducing weight by 0.18%. These outcomes confirm that the proposed MPSO provides competitive or superior performance compared to reference methods in both efficiency and solution quality.
کلیدواژه‌ها
Shape optimization؛ Truss structures؛ Particle swarm optimization؛ Modified particle swarm optimization
مراجع
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