TRUSS STRUCTURE OPTIMIZATION BASED ON IMPROVED WOLF PACK ALGORITHM

Authors

  • Yan-cang Li Hebei University of Engineering, College of Water Conservancy and Hydroelectric Power, No. 199 Guangmin South Street, Handan, China
  • Zong-jin Yang Hebei University of engineering, College of Civil Engineering, No. 199 Guangmin South Street, Handan, China
  • Cheng-hua Dang Corresponsing author, Hebei University of engineering, No. 199 Guangmin South Street, Handan, China

DOI:

https://doi.org/10.14311/CEJ.2019.04.0040

Keywords:

Wolf pack algorithm, Improved wolf pack algorithm, Truss optimization, Chaos thought

Abstract

Aiming at the optimization of truss structure, a wolf pack algorithm based on chaos and improved search strategy was proposed. The mathematical model of truss optimization was constructed, and the classical truss structure was optimized. The results were compared with those of other optimization algorithms. When selecting and updating the initial position of wolves, chaos idea was used to distribute the initial value evenly in the solution space; phase factor was introduced to optimize the formula of wolf detection; information interaction between wolves is increased and the number of runs is reduced. The numerical results show that the improved wolf pack algorithm has the characteristics of fewer parameters, simple programming, easy implementation, fast convergence speed, and can quickly find the optimal solution. It is suitable for the optimization design of the section size of space truss structures.

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References

Mathias S. Jørgensen, Uffe F. Larsen, Karsten W. Jacobsen, et al., 2018. Exploration Versus Exploitation in Global Atomistic Structure Optimization. Journal of Physical Chemistry A, vol. 122, no. 5: 1504-1509.

Pirmohammad S, Marzdashti S E., 2018. Crashworthiness Optimization of Combined Straight-tapered Tubes Using Genetic Algorithm and Neural Networks. Thin-Walled Structures, vol. 127: 318-332.

Imran M M, Mazhar F, Ahmad R., 2016. Multivariate Optimization of Fiber Reinforced Laminate Using Ant Colony Optimization Algorithm. Materials Science Forum, vol. 867: 116-120.

El-Shorbagy, M.A, Hassanien A E., 2018. Particle Swarm Optimization from Theory to Applications. International Journal of Rough Sets and Data Analysis, vol. 5, no. 2: 1-24.

Nguyen T T , Vo D N ., 2018. The Application of an Effective Cuckoo Search Algorithm for Optimal Scheduling of Hydrothermal System Considering Transmission Constraints. Neural Computing & Applications, vol. 9: 1-22.

Yang Chenguang, Tu Xuyan, Chen Jie., 2007. Algorithm of Marriage in Honey Bees Optimization Based on the Wolf Pack Search. International Conference of the International Conference on Intelligent Pervasive Computing, 462-467.

Rui Tang, Simon Fong, Xin She Yang, et al., 2012. Wolf Search Algorithm With Ephemeral Memory. Seventh International Conference on Digital Information Management, 165-172.

Simon Fong, Suash Deb, XinShe Yang, et al., 2015 A Heuristic Optimization Method Inspired by Wolf Preying Behavior. Neural Computing & Applications, vol. 26, no. 7: 1725-1738.

Wu Husheng, Zhang Fengming, Wu Lushan., 2013. New Swarm Intelligence Algorithm-wolf Pack Algorithm. Systems Engineering and Electronics., vol. 35, no. 11: 2430-2438.

Komaki G M, Kayvanfar V., 2015. Grey Wolf Optimizer Algorithm for the Two-stage Assembly Flow Shop Scheduling Problem with Release Time. Journal of Computational Science, vol. 8: 109-120.

Mirjalili S, Saremi S, Mirjalili S M, et al., 2016. Multi-objective Grey Wolf Optimizer: A novel Algorithm for Multi-criterion Optimization. Expert Systems with Applications, vol. 47: 106-119.

Sharma Y, Saikia L C., 2015. Automatic Generation Control of a Multi-area ST – Thermal Power System Using Grey Wolf Optimizer Algorithm Based Classical Controllers. International Journal of Electrical Power and Energy Systems, vol. 73: 853-862.

Radu Emil Precup, Radu Codrut David, Emil M Petriu., 2016. Grey Wolf Optimizer Algorithm-Based Tuning of Fuzzy Control Systems With Reduced Parametric Sensitivity. IEEE Transactions on Industrial Electronics, vol. 64, no.1: 527-534.

Shubham G, Kusum D., 2018. Cauchy Grey Wolf Optimiser for Continuous Optimisation Problems. Journal of Experimental and Theoretical Artificial Intelligence, vol. 30, no. 6: 1051-1075.

Shankar Chakraborty, Ankan Mitra., 2018 Parametric Optimization of Abrasive Water-jet Machining Processes Using Grey Wolf Optimizer. Materials and Manufacturing Processes, vol. 33, no.13: 1-12.

Goulianas K, Margaris A, Refanidis I, et al., 2018. Solving Polynomial Systems Using a Fast Adaptive Back Propagation-type Neural Network Algorithm. European Journal of Applied Mathematics, vol.29, no. 2: 301-337.

Wu Husheng, Zhang Fengming, Li Hao, et al., 2015. Discrete Wolf Pack Algorithm for Traveling Salesman Problem. Control and Decision, 30(10): 136-142.

Lu Dai, Fuling Guan, James K.Guest., 2014.Structural Optimization and Model Fabrication of a Double-Ring Deployable Antenna Truss. Acta Astronautica, vol. 94, no. 2: 843-851.

Kaveh A, Azar B F, Hadidi A, et al., 2010.Performance-based Seismic Design of Steel Frames Using Ant Colony Optimization. Steel Construction, vol. 66, no. 4: 566-574.

Teke T, Pekcan O., 2013. A Bat-inspired Algorithm for Structural Optimization. Computers & Structures, vol. 128, no. 128:77-90.

Assimi H, Jamali A, Nariman-Zadeh N., 2018.Multi-objective Sizing and Topology Optimization of Truss Structures Using Genetic Programming Based on a New Adaptive Mutant Operator. Neural Computing & Applications, vol. 23–24: 1-21.

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Published

2019-12-31

How to Cite

Li, Y.- cang, Yang, Z.- jin, & Dang, C.- hua. (2019). TRUSS STRUCTURE OPTIMIZATION BASED ON IMPROVED WOLF PACK ALGORITHM. Stavební Obzor - Civil Engineering Journal, 28(4). https://doi.org/10.14311/CEJ.2019.04.0040

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Articles