• Advances in Computational Design
• /
• v.2 no.3
• /
• pp.195-210
• /
• 2017

Simultaneous optimization of trusses which concurrently takes into account design variables related to the size, shape and topology of the structure is recognized as highly complex optimization problems. In this class of optimization problems, it is possible to encounter several unstable mechanisms throughout the solution process. However, to obtain a feasible solution, these unstable mechanisms somehow should be rejected from the set of candidate solutions. This study proposes triangular unit based method (TUBM) instead of ground structure method, which is conventionally used in the topology optimization, to decrease the complexity of search space of simultaneous optimization of the planar truss structures. TUBM considers stability of the triangular units for 2 dimensional truss systems. In addition, integrated particle swarm optimizer (iPSO) strengthened with robust technique so called improved fly-back mechanism is employed as the optimizer tool to obtain the solution for these class of problems. The results obtained in this study show the applicability and efficiency of the TUBM combined with iPSO for the simultaneous optimization of planar truss structures.

• Steel and Composite Structures
• /
• v.19 no.1
• /
• pp.43-58
• /
• 2015

There are many studies on the optimization of steel trusses in literature; and, a large number of them include a shape optimization. However, only a few of these studies are focused on the prestressed steel trusses. Therefore, this paper aims to determine the amounts of the material and cost savings in steel plane trusses in the case of prestressing. A parallel-chord simply supported steel truss is handled as an example to evaluate the used approach. It is considered that prestressing tendon is settled under the bottom bar, between two end supports, using deviators. Cross-sections of the truss members and height of the truss are taken as the design variables. The prestress losses are calculated in two steps as instantaneous losses and time-dependent losses. Tension increment in prestressing tendon due to the external loads is also considered. A computer program based on genetic algorithm is developed to solve the optimization problem. The handled truss is optimized for different span lengths and different tendon eccentricities using the coded program. The effects of span length and eccentricity of tendon on prestressed truss optimization are investigated. The results of different solutions are compared with each other and those of the non-prestressed solution. It is concluded that the amounts of the material and the cost of a steel plane truss can be reduced up to 19.9% and 14.6%, respectively, by applying prestressing.

• Structural Engineering and Mechanics
• /
• v.53 no.4
• /
• pp.833-845
• /
• 2015

Natural frequencies of the structural systems should be far away from the excitation frequency in order to avoid or reduce the destructive effects of dynamic loads on structures. To accomplish this goal, a structural optimization on size and shape has been performed considering frequency constraints. Such an optimization problem has highly nonlinear property. Thus, the quality of the solution is not independent of the optimization technique to be applied. This study presents the performance evaluation of the recently proposed meta-heuristic algorithm called Teaching Learning Based Optimization (TLBO) as an optimization engine in the weight optimization of the truss structures under frequency constraints. Some examples regarding the optimization of trusses on shape and size with frequency constraints are solved. Also, the results obtained are tabulated for comparison. The results demonstrated that the performance of the TLBO is satisfactory. Additionally, TLBO is better than other methods in some cases.

• Structural Engineering and Mechanics
• /
• v.53 no.5
• /
• pp.847-865
• /
• 2015

This paper presents the application of a recently developed meta-heuristic algorithm, called Colliding Bodies Optimization (CBO), for size and topology optimization of steel trusses. This method is based on the one-dimensional collisions between two bodies, where each agent solution is considered as a body. The performance of the proposed algorithm is investigated through four benchmark trusses for minimum weight with static and dynamic constraints. A comparison of the numerical results of the CBO with those of other available algorithms indicates that the proposed technique is capable of locating promising solutions using lesser or identical computational effort, with no need for internal parameter tuning.

• Journal of Korean Association for Spatial Structures
• /
• v.3 no.3 s.9
• /
• pp.67-74
• /
• 2003

The purpose of this study is to improve convergence speed of topology optimization procedure using the existing ESO method and to deal with topology decision of the truss structures according to a boundary condition, such as cantilever type. At the existing ESO topology optimization procedure for the truss structures, the adjustment of member sizes according to target stress has been executed by increasing or reducing a very small value from each member size. In this case, it takes too much iteration till convergence. Accordingly, it is practically hard to obtain optimum topology for a large scale structures. For that reason, it is necessary to improve convergence speed of ESO method more effectively. During the topology decision procedure, member sizes are adjusted by calculating approximate solution for member sizes corresponding to the target stress at every step, the new member sizes are adjusted by such method are applied in FEA procedure of next step.

• Structural Engineering and Mechanics
• /
• v.60 no.6
• /
• pp.1093-1117
• /
• 2016

Global sensitivity analysis (GSA) has been widely used to investigate the sensitivity of the model output with respect to its input parameters. In this paper a new single-solution search optimization algorithm is developed based on the GSA, and applied to the size optimization of truss structures. In this method the search space of the optimization is determined using the sensitivity indicator of variables. Unlike the common meta-heuristic algorithms, where all the variables are simultaneously changed in the optimization process, in this approach the sensitive variables of solution are iteratively changed more rapidly than the less sensitive ones in the search space. Comparisons of the present results with those of some previous population-based meta-heuristic algorithms demonstrate its capability, especially for decreasing the number of fitness functions evaluations, in solving the presented benchmark problems.

• Structural Engineering and Mechanics
• /
• v.44 no.3
• /
• pp.379-403
• /
• 2012

In recent years, the need for optimal design of structures under time-history loading aroused great attention in researchers. The main problem in this field is the extremely high computational demand of time-history analyses, which may convert the solution algorithm to an illogical one. In this paper, a new framework is developed to solve the size optimization problem of steel truss structures subjected to ground motions. In order to solve this problem, the covariance matrix adaptation evolution strategy algorithm is employed for the optimization procedure, while a generalized regression neural network is utilized as a meta-model for fitness approximation. Moreover, the computational cost of time-history analysis is decreased through a wavelet analysis. Capability and efficiency of the proposed framework is investigated via two design examples, comprising of a tower truss and a footbridge truss.

• Advances in Computational Design
• /
• v.2 no.4
• /
• pp.313-331
• /
• 2017

In this study, teaching-learning based optimization (TLBO) is improved by incorporating model of multiple teachers, adaptive teaching factor, self-motivated learning, and learning through tutorial. Modified TLBO (MTLBO) is applied for simultaneous topology, shape, and size optimization of space and planar trusses to study its effectiveness. All the benchmark problems are subjected to stress, displacement, and kinematic stability constraints while design variables are discrete and continuous. Analyses of unacceptable and singular topologies are prohibited by seeing element connectivity through Grubler's criterion and the positive definiteness. Performance of MTLBO is compared to TLBO and state-of-the-art algorithms available in literature, such as a genetic algorithm (GA), improved GA, force method and GA, ant colony optimization, adaptive multi-population differential evolution, a firefly algorithm, group search optimization (GSO), improved GSO, and intelligent garbage can decision-making model evolution algorithm. It is observed that MTLBO has performed better or found nearly the same optimum solutions.

• Proceeding of KASS Symposium
• /
• 2008.05a
• /
• pp.107-112
• /
• 2008

This paper investigates the variation of post-buckling behaviours of 2-dimensional shallow arch type truss after sizing optimization. The mathematical programming technique is used to produce the optimum member size of 2D arch truss against a central point load. Total weight of structure is considered as the objective function to be minimized and the displacement occurred at loading point and member stresses of truss are used as the constraint functions. The finite difference method is used to calculate the design sensitivity of objective function with respect to design variables. The postbuckling analysis carried out by using the geometrically nonlinear finite element analysis code ISADO-GN. It is found to be that there is a huge change of post-buckling behaviour between the initial structure and optimum structure. Numerical results can be used as useful information for future research of large spatial structures.

• Journal of Ship and Ocean Technology
• /
• v.5 no.2
• /
• pp.14-26
• /
• 2001

This paper presents a novel design approach that could generate structural design alternatives having different topologies and then, select the optimum structure from them with simulataneously determining its optimum design variables related to geometry and the member size subjected to the multiple objective design environments. For this purpose, a specialized genetic algorithm, called StrGA_DeAl + MOGA, which can handle the design alternatives and multi-criteria problems very effectively, is developed for the optimal structural design. To validate the developed method, method, plain truss design problems are considered as illustrative example. To begin with, some possible topological of the truss structure are suggested based on the stability criterion that should be satisfied under the given loading condition. Then, with the consideration of the given multi-criteria, several different topology forms are selected as design alternatives for the second step of the conceptual design process. Based on the chosen topolgy of truss structures, the sizing or shaping optimization process starts to determine the optimum design parameters. Ten-bar truss problems are given in the paper to confirm the above concept and methodology.