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Yassami, mohammad, Ashtari, Payam. (1401). PSOHHO Hybrid Optimization Algorithm for Truss Optimization. نشریه مهندسی عمران امیرکبیر, 6(2), 295-318. doi: 10.22060/ajce.2023.21732.5810
mohammad Yassami; Payam Ashtari. "PSOHHO Hybrid Optimization Algorithm for Truss Optimization". نشریه مهندسی عمران امیرکبیر, 6, 2, 1401, 295-318. doi: 10.22060/ajce.2023.21732.5810
Yassami, mohammad, Ashtari, Payam. (1401). 'PSOHHO Hybrid Optimization Algorithm for Truss Optimization', نشریه مهندسی عمران امیرکبیر, 6(2), pp. 295-318. doi: 10.22060/ajce.2023.21732.5810
Yassami, mohammad, Ashtari, Payam. PSOHHO Hybrid Optimization Algorithm for Truss Optimization. نشریه مهندسی عمران امیرکبیر, 1401; 6(2): 295-318. doi: 10.22060/ajce.2023.21732.5810

PSOHHO Hybrid Optimization Algorithm for Truss Optimization

AUT Journal of Civil Engineering
دوره 6، شماره 2، شهریور 2022، صفحه 295-318    اصل مقاله (2.53 M)
نوع مقاله: Research Article
شناسه دیجیتال (DOI): 10.22060/ajce.2023.21732.5810
نویسندگان
mohammad Yassami1؛ Payam Ashtari* 2
1Department of Engineering, Faculty of Civil Engineering, University of Zanjan, Zanjan, Iran.
2Department of Engineering, Faculty of Civil Engineering, University of Zanjan, Zanjan, Iran
چکیده
Numerous algorithms have recently been invented with varying strengths and weaknesses, none of which is the best for all cases. Herein, a hybrid optimization method known as a PSOHHO optimization algorithm is presented. There are two methods for combining algorithms: parallel and sequential. We adopted the parallel method and optimized the algorithm's performance. We cover the weaknesses of one algorithm with the strengths of another algorithm using a new method of combination. In this method, using several formulas, the top populations are exchanged between the two algorithms, and a new population is created. With this ability, the strengths of an algorithm can be used to compensate for the weaknesses of the other algorithm. In this method, no changes are made to the algorithms. The main goal is to use existing algorithms. This method aims to attain the optimal solution in the shortest time possible. Two algorithms of particle swarm optimization (PSO) and Harris Hawks optimization (HHO) were used to present this method and five truss samples were considered to confirm the performance of this method. Based on the results, this method has rapid convergence speed and acceptable results compared to the other methods. It also yields better results than its basic algorithms.
کلیدواژه‌ها
Meta-heuristic algorithms؛ Hybrid algorithm؛ Optimization؛ Truss؛ PSOHHO
مراجع
  1. B. Fogel, Evolutionary Computation: Toward a New Philosophy of Machine Intelligence, 3rd Editio ed., John Wiley & Sons, Inc., Hoboken, NJ, USA, 2005.
  2. Yao, Evolutionary Computation: Theory and Applications, in: Evolutionary Computation: Theory and Applications, WORLD SCIENTIFIC, 1999, pp. 1-36.
  3. Khalilpourazari, S. Khalilpourazary, A lexicographic weighted Tchebycheff approach for multi-constrained multi-objective optimization of the surface grinding process, Engineering Optimization, 49 (2017) 878-895.
  4. H. Holland, Genetic Algorithms, Scientific American, 267 (1992) 66-73.
  5. H. Holland, J.S. Reitman, Cognitive systems based on adaptive algorithms, ACM SIGART Bulletin, (1977) 49-49.
  6. Kennedy, R. Eberhart, Particle swarm optimization, in: Proceedings of ICNN'95 - International Conference on Neural Networks, IEEE, 1995, pp. 1942-1948.
  7. Kennedy, R.C. Eberhart, Swarm Intelligence, 1 st ed., Morgan Kaufmann, 2002.
  8. Eberhart, J. Kennedy, A new optimizer using particle swarm theory, in: MHS'95. Proceedings of the Sixth International Symposium on Micro Machine and Human Science, IEEE, 1995, pp. 39-43.
  9. A. Heidari, S. Mirjalili, H. Faris, I. Aljarah, M. Mafarja, H. Chen, Harris Hawks optimization: Algorithm and applications, Future Generation Computer Systems, 97 (2019) 849-872.
  10. Kaveh, S. Talatahari, A novel heuristic optimization method: charged system search, Acta Mechanica, 213 (2010) 267-289.
  11. Karaboga, B. Basturk, A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm, Journal of Global Optimization, 39 (2007) 459-471.
  12. Mirjalili, S.M. Mirjalili, A. Lewis, Grey Wolf Optimizer, Advances in Engineering Software, 69 (2014) 46-61.
  13. Yapici, N. Cetinkaya, A new meta-heuristic optimizer: Pathfinder algorithm, Applied Soft Computing, 78 (2019) 545-568.
  14. H. Samareh Moosavi, V.K. Bardsiri, Poor and rich optimization algorithm: A new human-based and multi populations algorithm, Engineering Applications of Artificial Intelligence, 86 (2019) 165-181.
  15. d.S. Coelho, Gaussian quantum-behaved particle swarm optimization approaches for constrained engineering design problems, Expert Systems with Applications, 37 (2010) 1676-1683.
  16. Civicioglu, E. Besdok, M.A. Gunen, U.H. Atasever, Weighted differential evolution algorithm for numerical function optimization: a comparative study with cuckoo search, artificial bee colony, adaptive differential evolution, and backtracking search optimization algorithms, Neural Computing and Applications, 32 (2020) 3923-3937.
  17. Kohler, M.M.B.R. Vellasco, R. Tanscheit, PSO+: A new particle swarm optimization algorithm for constrained problems, Applied Soft Computing, 85 (2019) 105865.
  18. H. Pakzad-Moghaddam, H. Mina, P. Mostafazadeh, A novel optimization booster algorithm, Computers & Industrial Engineering, 136 (2019) 591-613.
  19. Kaveh, A. Zolghadr, Cyclical parthenogenesis algorithm for layout optimization of truss structures with frequency constraints, Engineering Optimization, 49 (2017) 1317-1334.
  20. O. Degertekin, L. Lamberti, I.B. Ugur, Sizing, layout and topology design optimization of truss structures using the Jaya algorithm, Applied Soft Computing, 70 (2018) 903-928.
  21. Kaveh, P. Zakian, Improved GWO algorithm for optimal design of truss structures, Engineering with Computers, 34 (2018) 685-707.
  22. Aslani, P. Ghasemi, A.H. Gandomi, Constrained mean-variance mapping optimization for truss optimization problems, The Structural Design of Tall and Special Buildings, 27 (2018) e1449.
  23. Khatibinia, H. Yazdani, Accelerated multi-gravitational search algorithm for size optimization of truss structures, Swarm and Evolutionary Computation, 38 (2018) 109-119.
  24. Talatahari, A.H. Gandomi, G.J. Yun, Optimum design of tower structures using Firefly Algorithm, The Structural Design of Tall and Special Buildings, 23 (2014) 350-361.
  25. Pierezan, L. dos Santos Coelho, V. Cocco Mariani, E. Hochsteiner de Vasconcelos Segundo, D. Prayogo, Chaotic coyote algorithm applied to truss optimization problems, Computers & Structures, 242 (2021) 106353.
  26. F. Eid, L. Garcia-Hernandez, A. Abraham, Spiral water cycle algorithm for solving multi-objective optimization and truss optimization problems, Engineering with Computers, 38 (2022) 963–973.
  27. K.J. Jawad, C. Ozturk, W. Dansheng, M. Mahmood, O. Al-Azzawi, A. Al-Jemely, Sizing and layout optimization of truss structures with artificial bee colony algorithm, Structures, 30 (2021) 546-559.
  28. O. Degertekin, G. Yalcin Bayar, L. Lamberti, Parameter free Jaya algorithm for truss sizing-layout optimization under natural frequency constraints, Computers & Structures, 245 (2021) 106461.
  29. Mortazavi, Size and layout optimization of truss structures with dynamic constraints using the interactive fuzzy search algorithm, Engineering Optimization, 53 (2021) 369-391.
  30. Shahabsafa, R. Fakhimi, W. Lei, S. He, J.R.R.A. Martins, T. Terlaky, L.F. Zuluaga, Truss topology design and sizing optimization with guaranteed kinematic stability, Structural and Multidisciplinary Optimization, 63 (2021) 21-38.
  31. K.J. Jawad, M. Mahmood, D. Wang, O. AL-Azzawi, A. AL-JAMELY, Heuristic dragonfly algorithm for optimal design of truss structures with discrete variables, Structures, 29 (2021) 843-862.
  32. Chelouah, P. Siarry, Genetic and Nelder–Mead algorithms hybridized for a more accurate global optimization of continuous multiminima functions, European Journal of Operational Research, 148 (2003) 335-348.
  33. -K.S. Fan, E. Zahara, A hybrid simplex search and particle swarm optimization for unconstrained optimization, European Journal of Operational Research, 181 (2007) 527-548.
  34. M. Yaseen, M.F. Allawi, H. Karami, M. Ehteram, S. Farzin, A.N. Ahmed, S.B. Koting, N.S. Mohd, W.Z.B. Jaafar, H.A. Afan, A. El-Shafie, A hybrid bat–swarm algorithm for optimizing dam and reservoir operation, Neural Computing and Applications, 31 (2019) 8807-8821.
  35. Nenavath, R.K. Jatoth, Hybrid SCA–TLBO: a novel optimization algorithm for global optimization and visual tracking, Neural Computing and Applications, 31 (2019) 5497-5526.
  36. Devarapalli, V. Kumar, Power system oscillation damping controller design: A novel approach of integrated HHO-PSO algorithm, Archives of Control Sciences, 31 (2021) 553-591.
  37. Li, Y. Peng, S. Zhou, IMPROVED PSO ALGORITHM FOR SHAPE AND SIZING OPTIMIZATION OF TRUSS STRUCTURE, Journal of Civil Engineering and Management, 19 (2013) 542-549.
  38. A. Şenel, F. Gökçe, A.S. Yüksel, T. Yiğit, A novel hybrid PSO–GWO algorithm for optimization problems, Engineering with Computers, 35 (2019) 1359-1373.
  39. N. Chegini, A. Bagheri, F. Najafi, PSOSCALF: A new hybrid PSO based on Sine Cosine Algorithm and Levy flight for solving optimization problems, Applied Soft Computing, 73 (2018) 697-726.
  40. N. Trivedi, P. Jangir, A. Kumar, N. Jangir, R. Totlani, A Novel Hybrid PSO–WOA Algorithm for Global Numerical Functions Optimization, in: Advances in Computer and Computational Sciences 2018, pp. 53-60.
  41. Dhiman, A. Kaur, A Hybrid Algorithm Based on Particle Swarm and Spotted Hyena Optimizer for Global Optimization in: Soft Computing for Problem Solving, Springer Singapore, Singapore, 2019, pp. 599-615.
  42. Jiang, C. Zhang, S. Chen, Sequential Hybrid Particle Swarm Optimization and Gravitational Search Algorithm with Dependent Random Coefficients, Mathematical Problems in Engineering, 2020 (2020) 1-17.
  43. Dhawale, V.K. Kamboj, P. Anand, An improved Chaotic Harris Hawks Optimizer for solving numerical and engineering optimization problems, Engineering with Computers, (2021).
  44. Kaveh, P. Rahmani, A.D. Eslamlou, An efficient hybrid approach based on Harris Hawks optimization and imperialist competitive algorithm for structural optimization, Engineering with Computers, 38 (2022) 1555-1583.
  45. Abd Elaziz, D. Yousri, S. Mirjalili, A hybrid Harris hawks-moth-flame optimization algorithm including fractional-order chaos maps and evolutionary population dynamics, Advances in Engineering Software, 154 (2021) 102973.
  46. Abdel-Basset, W. Ding, D. El-Shahat, A hybrid Harris Hawks optimization algorithm with simulated annealing for feature selection, Artificial Intelligence Review, 54 (2021) 593-637.
  47. Al-Wajih, S.J. Abdulkadir, N. Aziz, Q. Al-Tashi, N. Talpur, Hybrid Binary Grey Wolf With Harris Hawks Optimizer for Feature Selection, IEEE Access, 9 (2021) 31662-31677.
  48. Yokota, T. Taguchi, M. Gen, A solution method for optimal weight design problem of 10 bar truss using genetic algorithms, Computers & Industrial Engineering, 35 (1998) 367-372.
  49. Awad, Sizing optimization of truss structures using the political optimizer (PO) algorithm, Structures, 33 (2021) 4871-4894.
  50. Varaee, M.R. Ghasemi, Engineering optimization based on ideal gas molecular movement algorithm, Engineering with Computers, 33 (2017) 71-93.
  51. Kaveh, T. Bakhshpoori, A new metaheuristic for continuous structural optimization: water evaporation optimization, Structural and Multidisciplinary Optimization, 54 (2016) 23-43.
  52. Adil, B. Cengiz, Optimal design of truss structures using weighted superposition attraction algorithm, Engineering with Computers, 36 (2020) 965-979.
  53. Pouriyanezhad, H. Rahami, S.M. Mirhosseini, Truss optimization using eigenvectors of the covariance matrix, Engineering with Computers, 37 (2021) 2207-2224.
  54. Jafari, E. Salajegheh, J. Salajegheh, An efficient hybrid of elephant herding optimization and cultural algorithm for optimal design of trusses, Engineering with Computers, 35 (2019) 781-801.
  55. Dhiman, ESA: a hybrid bio-inspired metaheuristic optimization approach for engineering problems, Engineering with Computers, 37 (2021) 323-353.
  56. Kaveh, R. Mahdipour Moghanni, S.M. Javadi, Optimum design of large steel skeletal structures using chaotic firefly optimization algorithm based on the Gaussian map, Structural and Multidisciplinary Optimization, 60 (2019) 879-894.
  57. Cao, X. Qian, Z. Chen, H. Zhu, Enhanced particle swarm optimization for size and shape optimization of truss structures, Engineering Optimization, 49 (2017) 1939-1956.
  58. H. Gandomi, S. Talatahari, X.-S. Yang, S. Deb, Design optimization of truss structures using cuckoo search algorithm, The Structural Design of Tall and Special Buildings, 22 (2013) 1330-1349.
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