Sizing optimization of skeletal structures using teaching-learning based optimization

Vedat Toğan, Ali Mortazavi


Teaching Learning Based Optimization (TLBO) is one of the non-traditional techniques to simulate natural phenomena into a numerical algorithm. TLBO mimics teaching learning process occurring between a teacher and students in a classroom. A parameter named as teaching factor, TF, seems to be the only tuning parameter in TLBO. Although the value of the teaching factor, TF, is determined by an equation, the value of 1 or 2 has been used by the researchers for TF. This study intends to explore the effect of the variation of teaching factor TF on the performances of TLBO. This effect is demonstrated in solving structural optimization problems including truss and frame structures under the stress and displacement constraints. The results indicate that the variation of TF in the TLBO process does not change the results obtained at the end of the optimization procedure when the computational cost of TLBO is ignored.


Optimization; skeletal structures; teaching-learning based optimization; teaching factor; penalty function

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Saka, M.P., Optimum Design of Steel Frames Using Stochastic Search Techniques Based on Natural Phenomena: A Review. In: Topping B.H.V., editor, Civil Engineering Computation Tools and Techniques, Chapter 6, Saxe-Coburg Publication, Stirlingshire (2007). Crossref

Dede, T., Bekiroğlu, S. and Ayvaz, Y., Weight minimization of trusses with genetic algorithm. Applied Soft Computing, 11, 2565-2575 (2011). Crossref

Jenkins, W.M., A decimal-coded evolutionary algorithm for constrained optimization. Computers & Structures, 80, 471-480 (2002). Crossref

Rajeev, S. and Krishnamoorthy, C.S., Discrete optimization of structures using genetic algorithms. Journal of Structural Engineering, 118, 1233–1250 (1992). Crossref

Reynolds, B.J. and Azarm, S., A Multi-objective heuristic-based hybrid genetic algorithm. Mechanics Based Design of Structures and Machines, 30, 463-491 (2002). Crossref

Toğan, V. and Daloğlu, A., Shape and size optimization of 3d trusses with genetic algorithms. Technical Journal of Turkish Chamber of Civil Engineering, 17, 3809-3825 (2006).

Zhang, J., Wang, B., Niu, F. and Cheng, G., Design optimization of connection section for concentrated force diffusion. Mechanics Based Design of Structures and Machines, 43, 209-231 (2015). Crossref

Camp, C.V., Bichon, B.J. and Stovall, S.P., Design of steel frames using ant colony optimization. Journal of Structural Engineering, 131, 369–379 (2005). Crossref

Değertekin, S.O., Optimum design of frames using harmony search. Structural Multidisciplinary Optimization, 36, 393-401 (2008). Crossref

Eskandar, H., Sadollah, A. and Bahreininejad, A., Water cycle algorithm – A novel metaheuristic optimization method for solving constrained engineering optimization problems. Computers & Structures, 110, 151–166 (2012). Crossref

Geem, Z.W., Kim, J.H. and Loganathan, G.V., A new heuristic optimization algorithm: Harmony search. Simulation, 76, 60-68 (2001). Crossref

Karaboğa, D., An idea based on honey bee swarm for numerical optimization. Technical Report, TR06, Erciyes University (2005).

Kaveh, A. and Talatahari, S., An improved ant colony optimization for the design of planar steel frames. Engineering Structures, 32, 864-873 (2010). Crossref

Kaveh, A. and Talatahari, S., Optimum design of skeletal structures using imperialist competitive algorithm. Computers & Structures, 88, 1220–1229 (2010). Crossref

Kennedy, J. and Eberhart, R., Particle swarm optimization. Proc. IEEE international conference on neural networks, pp 1942–1948 (2005).

Sadollah, A., Bahreininejad, A., Eskandar, H. and Hamdi, M., Mine blast algorithm: A new population based algorithm for solving constrained engineering optimization problems. Applied Soft Computing, 13, 2592–2612 (2013). Crossref

Seyedpoor, S.M. and Salajegheh, J., Adaptive neuro-fuzzy inference system for high-speed computing in optimal shape design of arch dams subjected to earthquake loading. Mechanics Based Design of Structures and Machines, 37, 31-59 (2009). Crossref

Sönmez, M., Discrete optimum design of truss structures using artificial bee colony algorithm. Structural Multidisciplinary Optimization, 43, 85-97 (2011). Crossref

Zheng, Y.J., Water wave optimization: A new nature-inspired metaheuristic. Computers and Operations Research, 55, 1–11 (2015). Crossref

Hasançebi, O., Erdal, F. and Saka, M.P., Adaptive harmony search method for structural optimization. Journal of Structural Engineering, 136, 419-431 (2010). Crossref

Toğan, V. and Daloğlu, A., Optimization of 3d trusses with adaptive approach in genetic algorithms. Engineering Structures, 28, 1019–1027 (2006). Crossref

Toğan, V. and Daloğlu, A., An improved genetic algorithm with initial population strategy and self-adaptive member grouping. Computers & Structures, 86, 1204–1218 (2008). Crossref

Rao, R.V., Savsani, V.J. and Vakharia, D.P., Teaching–learning-based optimization: A novel method for constrained mechanical design optimization problems. Computer-Aided Design, 43, 303-315 (2011). Crossref

Camp, C.V. and Farshchin, M., Design of space trusses using modified teaching-learning based optimization. Engineering Structures, 62, 87-97 (2014). Crossref

Cheng, W., Liu, F. and Li, L.J., Size and Geometry Optimization of Trusses Using Teaching-Learning-Based Optimization. International Journal Optimization Civil Engineering, 3, 431-444 (2013).

Dede, T. and Ayvaz, Y., Combined size and shape optimization of structures with a new meta-heuristic algorithm. Applied Soft Computing, 28, 250-258 (2015). Crossref

Dede, T. and Toğan, V., A teaching learning based optimization for truss structures with frequency constraints. Structural Engineering and Mechanics, 53(4), 833-845 (2015). Crossref

Değertekin, S.O. and Hayalioğlu M.S., Sizing truss structures using teaching-learning-based optimization. Computers & Structures, 119, 177-188 (2013). Crossref

Rao, R.V. and Patel, V., An improved teaching-learning-based optimization algorithm for solving unconstrained optimization problems. Scientia Iranica, 20, 710-720 (2013).

Toğan, V., Design of planar steel frames using teaching–learning based optimization. Engineering Structures, 34, 225-232 (2012). Crossref

Dede, T., Optimum Design of Grillage structures to LRFD-AISC with teaching-learning based optimization. Structural Multidisciplinary Optimization, 48, 955–964 (2013). Crossref

Arora, J.S., Introduction to optimum design. Elsevier Academic Press, California (2011).

Wu, S.J. and Chow, P.T., Steady-state genetic algorithms for discrete optimization of trusses. Computers & Structures, 56, 979-991 (1995). Crossref

Lemonge, A.C.C. and Barbosa, H.J.C., An adaptive penalty scheme for genetic algorithms in structural optimization. International Journal for Numerical Methods in Engineering, 59, 703–736 (2004). Crossref

Capriles, P.V.S.Z., Fonseca, L.G., Barbosa, H.J.C. and Lemonge, A.C.C., Rank-based ant colony algorithms for truss weight minimization with discrete variables. Communnications in Numerical Methods in Engineering, 23, 553–575 (2007). Crossref

Sadollah, A., Bahreininejad, A., Eskandar, H. and Hamdi, M., Mine blast algorithm for optimization of truss structures with discrete variables. Computers & Structures, 102, 49–63 (2012). Crossref

Sadollah, A., Eskandar, H., Bahreininejad, A. and Kim, J.H., Water cycle, mine blast and improved mine blast algorithms for discrete sizing optimization of truss structures. Computers and Structures, 149, 1–16 (2015). Crossref

American Institute of Steel Construction Manual of Steel Construction: Load and Resistance Factor Design. 3rd ed. Chicago (2001).

Hasançebi, O., Çarbaş, S., Doğan, E., Erdal, F. and Saka, M.P., Performance evaluation of metaheuristic search techniques in the optimum design of real size pin jointed structures. Computers and Structures, 87, 284–302 (2009). Crossref

Kaveh, A. and Talatahari, S., A particle swarm ant colony optimization for truss structures with discrete variables. Journal of Constructional Steel Research, 65, 1558–68 (2009). Crossref



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