Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures

Xiao, Ayang; Wang, Benli; Sun, Chaoli; Zhang, Shijie; Yang, Zhenguo

doi:10.1155/2014/671872

Cited by 8 publications

(5 citation statements)

References 31 publications

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“…For the considered class of problems, the annealing simulation algorithm was also successfully applied in [8]. In papers [9,10], the particle swarm method was used for truss optimization problems stated in a mixed space of variables and its modifications were proposed, which allowed the authors to obtain a better convergence to the optimum. In [11], the problem of minimizing the weight of the truss structure using the artificial bee colony algorithm is considered.…”

Section: Literature Review and Problem Statementmentioning

confidence: 99%

“…CS X  In some cases, the system of stability constraints (10) to (12) can be simplified when only the Euler elastic buckling constraints for the rod elements are considered. Such constraints are formulated for all compressed structural member, in which axial compression occurs under the action of design load combinations of the ultimate limit states, 1, ,…”

Section: Statement Of the Problem And Algorithm Of Parametric Optimiz...mentioning

confidence: 99%

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Layout and cross-sectional size optimization of truss structures with mixed design variables based on gradient method

Peleshko,

Yurchenko,

Rusyn

2023

EEJET

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The object of the study was truss-type rod structures, which were investigated for the purpose of finding the optimal design solution in a mixed (continuous and discrete) space of variables. The parameters of the geometric scheme of the truss, as well as the dimensions of the cross-sections of its elements, were considered as design variables. The stated optimization problem is represented as a nonlinear programming task, in which the objective function and nonlinear constraints of the mathematical model are continuously differentiable functions of the design variables. The system of constraints includes strength and stability inequalities, formulated for the design cross-sections of the rod elements of the structure, which is subject to the effect of the design load combinations of the ultimate limit states. As a part of the system of constraints, the displacement constraints formulated for the specified structural nodes, which is subject to the action of design load combinations of the serviceability limit states, are considered. To solve the stated optimization problem, a method of the objective function gradient on the surface of active constraints was used, with the simultaneous elimination of residuals in the violated restrictions. For design variables, the variation of which must be performed according to a given set of possible discrete values, a discretization procedure for the optimal solution obtained in the continuous space of design variables is proposed. A comparison of the proposed optimization methodology with alternative metaheuristic methods and algorithms reported in the literature was performed. On the considered problem of parametric optimization of a 47-span tower structure, a design solution with a weight of 835,403 kg was obtained, which is 1.53...4.6 % better than the optimal solutions obtained by other authors

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Section: Literature Review and Problem Statementmentioning

confidence: 99%

Section: Statement Of the Problem And Algorithm Of Parametric Optimiz...mentioning

confidence: 99%

Layout and cross-sectional size optimization of truss structures with mixed design variables based on gradient method

Peleshko,

Yurchenko,

Rusyn

2023

EEJET

View full text Add to dashboard Cite

show abstract

“…To solve such problems, recent studies have focused on the development of heuristic optimization techniques, such as genetic algorithms (GAs) [16,17], particle swarm optimization (PSO) [18][19][20], ant colony optimization (ACO) [21,22], big bang-big crunch (BB-BC) [23,24], imperialist competitive algorithm (ICA) [25], and charged system search (CSS) [26]. These algorithms can overcome most of the limitations found in traditional methods, such as becoming trapped in local minima and impractical computational complexity [27,28].…”

Section: Mathematical Problems In Engineeringmentioning

confidence: 99%

Reliability-Based Design Optimization for Crane Metallic Structure Using ACO and AFOSM Based on China Standards

Fan

2015

Mathematical Problems in Engineering

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The design optimization of crane metallic structures is of great significance in reducing their weight and cost. Although it is known that uncertainties in the loads, geometry, dimensions, and materials of crane metallic structures are inherent and inevitable and that deterministic structural optimization can lead to an unreliable structure in practical applications, little amount of research on these factors has been reported. This paper considers a sensitivity analysis of uncertain variables and constructs a reliability-based design optimization model of an overhead traveling crane metallic structure. An advanced first-order second-moment method is used to calculate the reliability indices of probabilistic constraints at each design point. An effective ant colony optimization with a mutation local search is developed to achieve the global optimal solution. By applying our reliability-based design optimization to a realistic crane structure, we demonstrate that, compared with the practical design and the deterministic design optimization, the proposed method could find the lighter structure weight while satisfying the deterministic and probabilistic stress, deflection, and stiffness constraints and is therefore both feasible and effective.

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“…Gonçalves et al [3] have used discrete sizing variables with buckling constraints on 10, 37, and 20 bar truss examples in a few combinations of optimization types with great results. Authors in [4][5][6][7][8][9] included dynamic constraints for buckling in their research using various optimization methods in order to optimize different aspects of examples. Researchers in [10] presented the need for using buckling constraints on sizing optimization examples of planar and space trusses.…”

Section: Introductionmentioning

confidence: 99%

Effects of Structural Optimization on Practical Roof Truss Construction

Petrović¹,

Kostić²,

Marjanović³

et al. 2020

Applied Engineering Letters

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In truss structural optimization the most frequently optimized factor of a structure is its weight. The minimization of weight contributes not only to savings in material, but also in other aspects of the structure such as number of elements used, number of welds needed, outer surface area, etc. This research aims to show the difference in optimal solutions for four different topological cases of a typical trapezoidal roof truss looking at their effects on overall outer surface area. The truss layouts are optimized for sizing, and a combination of sizing and shape with a minimal weight objective function. In order to ensure the most practically applicable solutions the example optimized in this paper uses dynamic constraints for buckling, stress constraints, and nodal displacement constraints. The overall outer surface area for all cases is compared, as surface protection accounts for a substantial part of the total cost of roof truss construction. Optimal solutions show a lack of correlation between weight and surface area, which is discussed in the conclusion.

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Fitness Estimation Based Particle Swarm Optimization Algorithm for Layout Design of Truss Structures

Cited by 8 publications

References 31 publications

Layout and cross-sectional size optimization of truss structures with mixed design variables based on gradient method

Layout and cross-sectional size optimization of truss structures with mixed design variables based on gradient method

Reliability-Based Design Optimization for Crane Metallic Structure Using ACO and AFOSM Based on China Standards

Effects of Structural Optimization on Practical Roof Truss Construction

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