Abstract
The sine cosine algorithm (SCA) is a new meta-heuristic algorithm. It has been proven to be very competitive compared with other meta-heuristic algorithms and has attracted significant attention from researchers in different fields. At present, there is no research on the application of SCA in the truss structure. In order to solve the truss optimization problem, the following improvements are made to SCA in this paper. Firstly, a non-linear conversion parameter is set to replace the linear conversion parameter, so that the exploration area is better in line with the characteristics of the actual optimization situation. Secondly, the Lévy flight is employed to enhance the algorithm’s global search ability. Thirdly, a novel elite guidance strategy taking advantage of memory data is proposed to strengthen the local search ability. Finally, a greedy selection strategy is adopted for the selection of the candidate. Combining the finite element method, we apply ISCA to optimize the size, shape and topology of truss structures. The examples show that ISCA can use less calculation time, get better results, and also better stability. So, the ISCA is effective to solve the size, shape and topology optimization problems of truss structures.
Similar content being viewed by others
References
Abualigah L, Abd Elaziz M, Sumari P, Zong WG, Gandomi AH (2022) Reptile search algorithm (RSA): A nature-inspired meta-heuristic optimizer. Expert Systems with Applications 191:116158, DOI: https://doi.org/10.1016/j.eswa.2021.116158
Agushaka JO, Ezugwu AE, Abualigah L (2022) Dwarf mongoose optimization algorithm. Computer Methods in Applied Mechanics and Engineering 391:114570, DOI: https://doi.org/10.1016/j.cma.2022.114570
Attia AF, El-Sehiemy RA, Hasanien HM (2018) Optimal power flow solution in power systems using a novel Sine-Cosine algorithm. International Journal of Electrical Power & Energy Systems 99:331–343, DOI: https://doi.org/10.1016/j.ijepes.2018.01.024
Baghlani A, Makiabadi, MH, Sarcheshmehpour M (2014) Discrete optimum design of truss structures by an improved firefly algorithm. Advances in Structural Engineering 17(10):1517–1530, DOI: https://doi.org/10.1260/1369-4332.17.10.1517
Banerjee A, Nabi M (2017) Re-entry trajectory optimization for space shuttle using sine-cosine algorithm. 8th International Conference on Recent Advances in Space Technologies, June 19–22, Istanbul, Turkey
Bureerat S, Pholdee N (2016) Optimal truss sizing using an adaptive differential evolution algorithm. Journal of Computing in Civil Engineering 30(2):04015019, DOI: https://doi.org/10.1061/(ASCE)CP.1943-5487.0000487
Chechkin AV, Metzler R, Klafter J, Gonchar VY (2008) Introduction to the theory of lévy flights. Foundations and Applications, John Wiley & Sons 129:129–162, DOI: https://doi.org/10.1002/9783527622979
Chegini SN, Bagheri A, Najafi F (2018) PSOSCALF: A new hybrid PSO based on sine cosine algorithm and lévy flight for solving optimization problems. Applied Soft Computing Journal 73:697–726, DOI: https://doi.org/10.1016/j.asoc.2018.09.019
Deb K, Gulati S (2001) Design of truss-structures for minimum weight using genetic algorithms. Finite Elements in Analysis and Design 37(5):447–465, DOI: https://doi.org/10.1016/S0168-874X(00)00057-3
Degertekin SO, Lamberti L, Ugur IB (2019) Discrete sizing/layout/topology optimization of truss structures with an advanced Jaya algorithm. Applied Soft Computing 79:363–390, DOI: https://doi.org/10.1016/j.asoc.2019.03.058
Dueck G, Tobias S (1990) Threshold accepting: A general purpose optimization algorithm appearing superior to simulated annealing. Journal of Computational Physics 90(1):161–175, DOI: https://doi.org/10.1016/0021-9991(90)90201-B
Erol OK, Ibrahim E (2006) A new optimization method: Big bang-big crunch. Advances in Engineering Software 37(2):106–111, DOI: https://doi.org/10.1016/j.advengsoft.2005.04.005
Ewees AA, Abd EM, Al-Qaness MA, Khalil HA, Kim S (2020) Improved artificial bee colony using sine-cosine algorithm for multi-level thresholding image segmentation. IEEE Access 8:26304–26315, DOI: https://doi.org/10.1109/ACCESS.2020.2971249
Gonçalves MS, Lopez RH, Miguel LFF (2015) Search group algorithm: A new meta-heuristic method for the optimization of truss structures. Computers & Structures 153:165–184, DOI: https://doi.org/10.1016/j.compstruc.2015.03.003
Gupta S, Deep K (2019a) Improved sine cosine algorithm with crossover scheme for global optimization. Knowledge-Based Systems 165: 374–406, DOI: https://doi.org/10.1016/j.knosys.2018.12.008
Gupta S, Deep K (2019b) A hybrid self-adaptive sine cosine algorithm with opposition based learning. Expert Systems with Applications 119:210–230, DOI: https://doi.org/10.1016/j.eswa.2018.10.050
Harsono K, Prayogo D, Prasetyo KE, Wong FT, Tjandra D (2020) Comparative study of particle swarm optimization algorithms in solving size, topology, and shape optimization. Journal of Physics: Conference Series, October 28–29, Yogyakarta, Indonesia
Hatamlou A (2013) Black hole: A new heuristic optimization approach for data clustering. Information Sciences 222:175–184, DOI: https://doi.org/10.1016/j.ins.2012.08.023
Holland JH (1992) Genetic algorithms. Scientific American 267(1):66–73, DOI: https://doi.org/10.1038/scientificamerican0792-66
Jahangiri M, Hadianfard MA, Najafgholipour MA, Jahangiri M, Gerami MR (2020) Interactive autodidactic school: A new meta-heuristic optimization algorithm for solving mathematical and structural design optimization problems. Computers & Structures 235:106268, DOI: https://doi.org/10.1016/j.compstruc.2020.106268
Kaveh A, Farhoudi N (2013) A new optimization method: Dolphin echolocation. Advances in Engineering Software 59:53–70, DOI: https://doi.org/10.1016/j.advengsoft.2013.03.004
Kaveh A, Ghazaan MI (2015) Hybridized optimization algorithms for design of trusses with multiple natural frequency constraints. Advances in Engineering Software 79:137–147, DOI: https://doi.org/10.1016/j.advengsoft.2014.10.001
Kaveh A, Javadi SM (2014) An efficient hybrid particle swarm strategy, ray optimizer, and harmony search algorithm for optimal design of truss structures. Periodica Polytechnica Civil Engineering 58(2): 155–171, DOI: https://doi.org/10.3311/PPci.7550
Kaveh A, Malakouti S (2010) Hybrid genetic algorithm and particle swarm optimization for the force method-based simultaneous analysis and design. Iranian Journal of Science and Technology 34:15–34
Kaveh A, Talatahari S (2010) A charged system search with a fly to boundary method for discrete optimum design of truss structures. Asian Journal of Civil Engineering 11(3):277–293, DOI: https://doi.org/10.1007/s12572-011-0034-y
Kaveh A, Vazirinia Y (2020) An upgraded sine cosine algorithm for tower crane selection and layout problem. Periodica Polytechnica Civil Engineering 64(2):325–343, DOI: https://doi.org/10.3311/PPci.15363
Kaveh A, Zolghadr A (2017) Cyclical parthenogenesis algorithm for layout optimization of truss structures with frequency constraints. Engineering Optimization 49(8):1317–1334, DOI: https://doi.org/10.1080/0305215X.2016.1245730
Kumar S, Tejani GG, Pholdee N, Bureerat S (2022) Performance enhancement of meta-heuristics through random mutation and simulated annealing-based selection for concurrent topology and sizing optimization of truss structures. Soft Computing 26(12):5661–5683, DOI: https://doi.org/10.1007/s00500-022-06930-2
Li J, Liu F (2011) Group search optimization for applications in structural design. Springer, 9, DOI: https://doi.org/10.1007/978-3-642-20536-1
Long W, Wu T, Liang X, Xu S (2019) Solving high-dimensional global optimization problems using an improved sine cosine algorithm. Expert Systems with Applications 123:108–126, DOI: https://doi.org/10.1016/j.eswa.2018.11.032
Majhi SK (2018) An efficient feed foreword network model with sine cosine algorithm for breast cancer classification. International Journal of System Dynamics Applications 7(2):1–14, DOI: https://doi.org/10.4018/IJSDA.2018040101
Miguel LFF, Lopez RH, Miguel LFF (2013) Multimodal size, shape, and topology optimisation of truss structures using the Firefly algorithm. Advances in Engineering Software 56:23–37, DOI: https://doi.org/10.1016/j.advengsoft.2012.11.006
Mirjalili S (2016) SCA: A sine cosine algorithm for solving optimization problems. Knowledge-based Systems 96:120–133, DOI: https://doi.org/10.1016/j.knosys.2015.12.022
Oyelade ON, Ezugwu AES, Mohamed TIA, Abualigah L (2022) Ebola optimization search algorithm: A new nature-inspired metaheuristic optimization algorithm. IEEE Access 2022(10):16150–16177, DOI: https://doi.org/10.1109/ACCESS.2022.3147821
Price KV (1996) Differential evolution: A fast and simple numerical optimizer. Biennial Conference of the North American Fuzzy Information Processing Society, June, New York, United States
Qu C, Zeng Z, Dai J, Yi Z, He W (2018) A modified sine-cosine algorithm based on neighborhood search and greedy lévy mutation. Computational Intelligence and Neuroscience 2018:1–19, DOI: https://doi.org/10.1155/2018/4231647
Rahami H, Kaveh A, Gholipour Y (2008) Sizing, geometry and topology optimization of trusses via force method and genetic algorithm. Engineering Structures 30(9):2360–2369, DOI: https://doi.org/10.1016/j.engstruct.2008.01.012
Richardson JN, Adriaenssens S, Bouillard P, Coelho RF (2012) Multiobjective topology optimization of truss structures with kinematic stability repair. Structural and Multidisciplinary Optimization 46(4): 513–532, DOI: https://doi.org/10.1007/s00158-012-0777-5
Savsani VJ, Tejani GG, Patel VK, Poonam S (2017) Modified meta-heuristics using random mutation for truss topology optimization with static and dynamic constraints. Journal of Computational Design and Engineering 4(2):106–130, DOI: https://doi.org/10.1016/j.jcde.2016.10.002
Tang WY, Tong LY, Gu YX (2005) Improved genetic algorithm for design optimization of truss structures with sizing, shape and topology variables. International Journal for Numerical Methods in Engineering 62(13):1737–1762, DOI: https://doi.org/10.1002/nme.1244
Tejani GG, Savsani VJ, Patel VK (2016) Adaptive symbiotic organisms search (SOS) algorithm for structural design optimization. Journal of Computational Design and Engineering 3(3):226–249, DOI: https://doi.org/10.1016/j.jcde.2016.02.003
Tejani GG, Savsani VJ, Patel VK, Savsani PV (2018a) Size, shape, and topology optimization of planar and space trusses using mutation-based improved meta-heuristics. Journal of Computational Design and Engineering 5(2):198–214, DOI: https://doi.org/10.1016/j.jcde.2017.10.001
Tejani GG, Savsani VJ, Patel VK, Mirjalili S (2018b) Truss optimization with natural frequency bounds using improved symbiotic organisms search. Knowledge-Based Systems 143:162–178, DOI: https://doi.org/10.1016/j.knosys.2017.12.012
Tejani GG, Savsani VJ, Patel VK, Seyedali M (2019) An improved heat transfer search algorithm for unconstrained optimization problems. Journal of Computational Design and Engineering 6(1):13–32, DOI: https://doi.org/10.1016/j.jcde.2018.04.003
Wang J, Yang W, Du P, Niu T (2018) A novel hybrid forecasting system of wind speed based on a newly developed multi-objective sine cosine algorithm. Energy Conversion and Management 163:134–150, DOI: https://doi.org/10.1016/j.enconman.2018.02.012
Wang M, Guizhen L (2021) A modified sine cosine algorithm for solving optimization problems. IEEE Access 9:27434–27450, DOI: https://doi.org/10.1109/ACCESS.2021.3058128
Yang XS, Deb S (2013) Multiobjective cuckoo search for design optimization. Computers & Operations Research 40:1616–1624, DOI: https://doi.org/10.1016/j.cor.2011.09.026
Acknowledgments
Not Applicable
Author information
Authors and Affiliations
Corresponding author
Rights and permissions
About this article
Cite this article
Zhou, H., Yang, X., Tao, R. et al. Improved Sine-cosine Algorithm for the Optimization Design of Truss Structures. KSCE J Civ Eng 28, 687–698 (2024). https://doi.org/10.1007/s12205-023-0314-7
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12205-023-0314-7