DISCRETE AND CONTINUOUS DESIGN OPTIMIZATION OF TOWER STRUCTURES USING THE JAYA ALGORITHM

Yıl 2018, Cilt: 13 Sayı: 2, 134 - 144, 22.04.2018

S. Özgür Değertekin , Luciano Lamberti İ. Behram Ugur

Öz

            The
Jaya algorithm (JA) which is very recently developed metaheuristic method is
proposed for design optimization of tower structures. The distinctive
characteristic of JA is that it does not use algorithm-specific parameters. The
algorithm has a very simple formulation where the basic idea is to approach the
best solution and escape from the worst solution. Continuous design
optimization of 72-bar spatial tower and discrete design optimization of
244-bar spatial tower structure are used to demonstrate the validity of JA. The
results show that the JA can obtain better designs than those of the other
metaheuristic optimization methods in terms of optimized weight, standard
deviation and number of structural analyses. 

Anahtar Kelimeler

Design Optimization, Discrete Design Variables, Continuous Design Variables, Tower Structures, Jaya Algorithm

Kaynakça

• [1] Kaveh, A. and Talatahari, S., (2010). A Novel Heuristic Optimization Method: Charged System Search, Acta Mechanica, Volume: 213, Issue: 3, pp:267-289.
• [2] Yang, X.S., (2010). Firefly Algorithm, Stochastic Test Functions And Design Optimization, International Journal of Bio-Inspired Computation, Volume: 2, Issue: 2, pp:78-84.
• [3] Rao, R.V., Savsani, V.J., and Vakharia, D.P., (2011). Teaching–Learning-Based Optimization: a Novel Method for Constrained Mechanical Design Optimization Problems, Computer-Aided Design, Volume: 43, Issue: 3, pp:303-315.
• [4] Yang, X.S., (2012). Flower Pollination Algorithm for Global Optimization, pp:240-249, UCNC.
• [5] Neshat, M., Sepidnam, G., and Sargolzaei, M., (2013). Swallow Swarm Optimization Algorithm: A New Method to Optimization, [6] Neural Computing and Applications, Volume:3, Issue:2, pp:429-454.
• [7] Kaveh, A. and Bakhshpoori, T., (2016). Water Evaporation Optimization: a Novel Physically Inspired Optimization Algorithm, Computers & Structures, Volume: 167, pp:69-85.
• [8] Kaveh, A. and Talatahari, S., (2009). Size Optimization of Space Trusses Using Big Bang–Big Crunch Algorithm, Computers & Structures, Volume: 87, Issue: 17, pp:1129-1140.
• [9] Degertekin, S.O., (2012). Improved Harmony Search Algorithms for Sizing Optimization of Truss Structures, Computers & Structures, Volume: 92, pp:229-241.
• [10] Degertekin, S.O. and Hayalioglu, M.S., (2013). Sizing Truss Structures Using Teaching-Learning-Based Optimization, Computers & Structures, Volume: 119, pp:177-188.
• [11] Jalili, S. and Hosseinzadeh, Y., (2015). A Cultural Algorithm for Optimal Design of Truss Structures, Latin American Journal Of Solids and Structures, Volume: 12, Issue: 9, pp:1721-1747.
• [12] Toğan, V. and Daloğlu, A.T., (2006). Optimization of 3d Trusses with Adaptive Approach in Genetic Algorithms, Engineering Structures, Volume: 28, Issue: 7, pp:1019–1027.
• [13] Kaveh, A., Kalatjari, V.R., and Talebpour, M.H., (2016). Optimal Design of Steel Towers Using a Multi-Metaheuristic Based Search Method, Periodica Polytechnica. Civil Engineering, Volume: 60, Issue: 2, pp. 229-246.
• [14] Rao, R.V. (2016). Jaya: A simple and new optimization algorithm for solving constrained and unconstrained optimization problems, International Journal of Industrial Engineering Computations, Volume: 7, pp:19–34.
• [15] Rao, R.V., More, K.C., Taler, J., and Oclon, P., (2016). Dimensional Optimization of a Micro-Channel Heat Sink Using Jaya Algorithm, Applied Thermal Engineering, Volume: 103, pp:572-582.
• [16] Rao, R.V. and Waghmare, G.G., (2016). A New Optimization Algorithm for, Engineering Optimization, pp: 1-24.
• [17] Manual of steel construction-allowable stress design, (1989). 9th, American Institute of Steel Construction, AISC, Chicago.