Geometrically Nonlinear Analysis of Trusses Using Particle Swarm Optimization

Abstract

Particle swarm optimization (PSO) algorithm is a heuristic optimization technique based on colony intelligence, developed through inspiration from social behaviors of bird flocks and fish schools. It is widely used in problems in which the optimal value of an objective function is searched. Geometrically nonlinear analysis of trusses is a problem of this kind. The deflected shape of the truss where potential energy value is minimal is known to correspond to the stable equilibrium position of the system analyzed. The objective of this study is to explore the success of PSO using this minimum total potential energy principle, in finding good solutions to geometrically nonlinear truss problems. For this purpose analyses are conducted on three structures, two plane trusses and a space truss. The results obtained show that in case of using 20 or more particles, PSO produces very good and robust solutions.

SoftFEM: The Soft Finite Element Method

“…Alternative methods to GAs have also been proposed, to a lesser extent, such as sequential approximation optimization, evolutionary strategies, DE, PSO, harmony search, and EDAs…”

“…Similar application papers have also applied GA to computational fluid dynamics. 28,29 Alternative methods to GAs have also been proposed, to a lesser extent, such as sequential approximation optimization, 30 evolutionary strategies, 31,32 DE, 33 PSO, 34 harmony search, 35 and EDAs. 36 The use of local optimization methods has also been referred in the literature, being simulated annealing (SA) 37,38 one of the most common approaches, but other approaches such as VNS 39 and TS 40 have also been considered.…”

Modelling and Structural Design for Parallel Umbrella‐Shaped Cable‐Strut Structures Based on Stationary Potential Energy Principles

“…Currently, most research on structural design is focused on rigid structures, and many theories and methods have been proposed based on energy principles, e.g., a combination of the total complementary energy minimization theory and a modified sequential quadratic programming (SQP) algorithm discussed by Ohkubo et al [7], a metaheuristic algorithm developed by Toklu et al [8], and a particle swarm optimization (PSO) algorithm presented by Temür et al [9]. However, research on the structural design of large-span steel structures is lacking, with most of the current studies predominantly limited to trusses [10,11], as discussed by Kawamura et al [12].…”

Advanced energy‐based analyses of trusses employing hybrid metaheuristics

“…If a set of structural displacements corresponding to the minimum total potential energy is found, the solution of nonlinear problem can be found. As an application of black‐box type, total potential optimization using metaheuristic algorithms (TPO/MAs) was developed by Toklu . In this method, the design variables are the displacement parameters of the structural systems.…”

“…As an application of black-box type, total potential optimization using metaheuristic algorithms (TPO/MAs) was developed by Toklu. [10][11][12][13][14][15][16] In this method, the design variables are the displacement parameters of the structural systems. These design variables are randomly generated by using the rules of metaheuristic methods, and the corresponding total potential energy values are found.…”