Journal Menu
Last Edition
Journal information

Vol.1, No.4, 2022: pp.142-147



Nenad Petrović1
, Nenad Kostic1
, Nenad Marjanovic1
, Anja Velemir1
Ljubica Spasojević 1
1University of Kragujevac, Faculty of Engineering, Kragujevac, Serbia

Received: 04.07.2022.
Accepted: 12.10.2022.
Available: 31.12.2022.


This article aims to demonstrate the difference in results for minimal weight optimization for a 17 bar truss sizing and shape optimization problem. In order to attain results which can be produced in practice Euler bucking, minimal element length, maximal stress and maximal displacement constraints were used. Using the same initial setup, optimization was conducted using particle swarm optimization algorithm and compared to genetic algorithm. Optimal results for both algorithms are compared to initial values which are analytically calculated. The individual element lengths are observed, along with the overall weight, surface area and included number of different cross-sections.


Truss optimization, sizing and shape, minimal weight, element length


[1] N. Petrović, N. Kostić, N. Marjanović, V. Marjanović, Influence of Using Discrete Cross-Section Variables for All Types of Truss Structural Optimization with Dynamic Constraints for Buckling. Applied  Engineering Letters, 3(2), 2018: 78-83.
[2] H. Cao, W. Sun, Y. Chen, F. Kong, L. Feng, Sizing and Shape Optimization of Truss Employing a Hybrid Constraint-Handling Technique and Manta Ray Foraging Optimization. Expert Systems with Applications, 213(Part B), 2023: 118999.
[3] S. Anosri, N. Panagant, S. Bureerat, N. Pholdee, Success History Based Adaptive Multi-Objective Differential Evolution Variants with an Interval Scheme for Solving Simultaneous Topology, Shape and Sizing Truss Reliability Optimization. Knowledge-Based Systems, 253, 2022: 109533.
[4] S. Zheng, L. Qiu, F. Lan, TSO-GCN: A Graph Convolutional Network Approach for Real-Time and Generalizable Truss Structural Optimization. Applied Soft Computing, 134, 2023: 110015.
[5] M.S. Gonçalves, R.H. Lopez, L.F.F. Miguel, Search Group Algorithm: A New Metaheuristic Method for the Optimization of Truss Structures. Computers & Structures, 153, 2015: 165-184.
[6] H.-A. Pham, T.-D. Tran, Optimal Truss Sizing by Modified Rao Algorithm Combined with Feasible Boundary Search Method. Expert Systems with Applications, 191, 2022: 116337.
[7] M. Shahabsafa, A. Mohammad-Nezhad, T. Terlaky, L. Zuluaga, S. He, J.T. Hwang, J.R.R.A. Martins, A Novel Approach to Discrete Truss Design Problems Using Mixed Integer Neighborhood Search. Structural and Multidisciplinary Optimization, 58, 2018: 2411-2429.
[8] G. Bekdaş, S.M. Nigdeli, X.-S. Yang, Sizing optimization of truss structures using flower pollination algorithm. Applied Soft Computing, 37, 2015: 322-331.
[9] V. Ho-Huu, D. Duong-Gia, T. Vo-Duy, T. Le-Duc, T. Nguyen-Thoi, An Efficient Combination of Multi-Objective Evolutionary Optimization and Reliability Analysis for Reliability-Based Design Optimization of Truss Structures. Expert Systems with Applications, 102, 2018: 262-272.
[10] S. Gholizadeh, Layout Optimization of Truss Structures by Hybridizing Cellular Automata and Particle Swarm Optimization. Computers & Structures, 125, 2013: 86-99.
[11] H. Madah, O. Amir, Truss Optimization with Buckling Considerations Using Geometrically Nonlinear Beam Modeling. Computers & Structures, 192, 2017: 233-247.
[12] N. Petrović, V. Marjanović, N. Kostić, N. Marjanović, Means and Effects оf Constraining the Number of Used Cross-Sections in Truss Sizing Optimization. Transactions of FAMENA, 44(3), 2020: 35-46.
[13] J.P.G. Carvalho, A.C.C. Lemonge, É.C.R. Carvalho, P.H. Hallak, H.S. Bernardino, Truss Optimization with Multiple Frequency Constraints and Automatic Member Grouping. Structural and Multidisciplinary Optimization, 57, 2017: 547-577.
[14] E.G. Shopova, N.G. Vaklieva-Bancheva, BASIC-A Genetic Algorithm for Engineering Problems Solution. Computers & Chemical Engineering, 30(8), 2006: 1293-1309.
[15] B. Stojanović, S. Gajević, N. Kostić, S. Miladinović, A. Vencl, Optimization of Parameters that Affect Wear of A356/Al2O3 Nanocomposites Using RSM, ANN, GA and PSO Methods. Industrial Lubrication and Tribology, 74(3), 2022: 350-359.

© 2023 by the authors. This work is licensed under a Creative Commons Attribution-NonCommercial 4.0 International License (CC BY-NC 4.0)

Volume 2
Number 4
December 2023.



How to Cite

N. Petrović, N. Kostić, N. Marjanović, A. Velemir, L. Spasojević, Comparing Truss Sizing and Shape Optimization Effects for 17 Bar Truss Problem. Advanced Engineering Letters, 1(4), 2022: 142-147.

More Citation Formats

Petrović, N., Kostić, N., Marjanović, N., Velemir, A., & Spasojević, L. (2022). Comparing Truss Sizing and Shape Optimization Effects for 17 Bar Truss Problem. Advanced Engineering Letters1(4), 142-147.

Petrović, Nenad, et al. “Comparing Truss Sizing and Shape Optimization Effects for 17 Bar Truss Problem.” Advanced Engineering Letters, vol. 1, no. 4, 2022, pp. 142-47,

Petrović, Nenad, Nenad Kostić, Nenad Marjanović, Anja Velemir, and Ljubica Spasojević. 2022. “Comparing Truss Sizing and Shape Optimization Effects for 17 Bar Truss Problem.” Advanced Engineering Letters 1 (4): 142-47.

Petrović, N., Kostić, N., Marjanović, N., Velemir, A. and Spasojević, L. (2022). Comparing Truss Sizing and Shape Optimization Effects for 17 Bar Truss Problem. Advanced Engineering Letters, 1(4), pp.142-147. doi: 10.46793/adeletters.2022.1.4.4.