Research Article
BibTex RIS Cite

Yeni Bir Hibrid Metasezgisel Algoritma İle Drone Kolunun Yapısal Optimizasyonu

Year 2023, Volume: 21 Issue: 2, 74 - 80, 24.11.2023
https://doi.org/10.56193/matim.1302774

Abstract

Bu araştırmada, insansız hava taşıtlarından bir drone’a ait taşıyıcı kolu optimize etmek için yeni bir hibrit INFO-benzetimli tavlama algoritması (HINFO-BT) geliştirilmiş ve yeni geliştirilen yöntem şekil optimizasyonunda kullanılmıştır. Tasarımın ana amacı, stres kısıtlamalarını ihlal etmeden drone kolunun topoloji ve şekil optimizasyonu ile parça ağırlığı minimize etmektir. Şekil optimizasyonunda amaç ve kısıt fonksiyonlarının denklemlerini elde etmek için hem Latin hiperküp örnekleme metodolojisi hem de kriging meta-modelleme yaklaşımı kullanılmıştır. Optimal tasarım, tüm problem kısıtlarını karşılamakta ve drone kolunun başlangıç tasarımına göre ağırlığı %24.8 azalmıştır. Bu sonuçlar şekil optimizasyonu için önerilen yönteminin üstünlüğünü göstermektedir.

Supporting Institution

Bursa Uludağ Üniversitesi

Thanks

Bursa Uludağ Üniversitesi Bilimsel Araştırma Projeleri Koordinasyon Birimi(BAP)'a teşekkür ederim.

References

  • 1. Yap, Y. L., Toh, W., Giam, A., Yong, F. R., Chan, K. I., Tay, J. W. S., Ng, T. Y., “Topology optimization and 3D printing of micro-drone: Numerical design with experimental testing”, International Journal of Mechanical Sciences, 2023, vol.237, 107771.
  • 2. Rayed, A. M., Esakki, B., Ponnambalam, A., Banik, S. C., Aly, K., “Optimization of UAV structure and evaluation of vibrational and fatigue characteristics through simulation studies”, 2021, International Journal for Simulation and Multidisciplinary Design Optimization, Vol.12, 17.
  • 3. Palinkas, I., Pekez, J., Desnica, E., Rajic, A., Nedelcu, D., “Analysis and Optimization of UAV Frame Design for Manufacturing from Thermoplastic Materials on FDM 3D Printer”, 2021, Materiale Plastice, vol.58(4), pp.238-249.
  • 4. Nvss, S., Esakki, B., Yang, L. J., Udayagiri, C., Vepa, K. S., “Design and development of unibody quadcopter structure using optimization and additive manufacturing techniques”, 2022, Designs, vol.6(1), 8.
  • 5. Fang, H., Rais-Rohani, M., Liu, Z., “A comparative study of metamodeling methods for multiobjective crashworthiness optimization”, 2005, Computers and Structures, vol.83(25–26), pp.2121–2136.
  • 6. Kurtuluş, E., Yıldız, A.R., Sait, S.M., Bureerat, S., “A novel hybrid Harris hawks-simulated annealing algorithm and RBF-based metamodel for design optimization of highway guardrails”, 2020, Materials Testing, vol.62, pp.251-260.
  • 7. Gupta, S., Deep, K., “An efficient grey wolf optimizer with opposition-based learning and chaotic local search for integer and mixed-integer optimization problems”, 2019, Arabian Journal for Science and Engineering, vol.44, pp. 7277-7296.
  • 8. Gupta, S., Deep, K., “Optimal Coordination of Overcurrent Relays Using Improved Leadership-Based Grey Wolf Optimizer”, 2019, Arabian Journal for Science and Engineering, vol.45, pp.2081–2091.
  • 9. Pholdee, N., Bureerat, S.,Yildiz, A.R., “Hybrid real-code population-based incremental learning and differential evolution for many-objective optimisation of an automotive floor-frame”, 2017, International Journal of Vehicle Design, vol.73(1-3), pp. 20-53.
  • 10. Gupta, S., Deep, K., “Cauchy Grey Wolf Optimiser for continuous optimisation problems”, 2018, Journal of Experimental and Theoretical Artificial Intelligence, vol.30, pp.1051-1075.
  • 11. Gupta, S., Deep, K., “A novel hybrid sine cosine algorithm for global optimization and its application to train multilayer perceptrons”, 2019, Applied Intelligence, vol.50, pp.993-1026.
  • 12. Gupta, S., Deep, K., “A novel random walk grey wolf optimizer”, 2019, Swarm and Evolutionary Computation, vol.44, pp.101-112.
  • 13. Gupta, S., Deep, K., “A hybrid self-adaptive sine cosine algorithm with opposition based learning”, 2019, Expert Systems with Applications, vo.119, pp.210-230.
  • 14. Soh, H. J., Yoo, J. H., “Optimal shape design of a brake calliper for squeal noise reduction considering system instability”, 2010, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol.224(7), pp.909-925.
  • 15. Gupta, S., Deep, K., “Hybrid sine cosine artificial bee colony algorithm for global optimization and image segmentation”, 2019, Neural Computing and Applications, 1-23. doi:10.1007/s00521-019-04465-6
  • 16. Yildiz, B.S., Mehta, P., Sait, S.M., Panagant, N., Kumar, S., Yildiz, A.R., “A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems”, 2022, Materials Testing, vol.64(7), pp.1043-1050.
  • 17. Karaboga, D., Basturk, B., “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm”, 2007, Journal of Global Optimization, vol.39(3), pp.459–471.
  • 18. Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., Saremi, S., Faris, H., Mirjalili, S.M., “Multi verse Algorithm: A bio-inspired optimizer for engineering design problems”, 2017, Advances in Engineering Software, vol.114, pp.163-191.
  • 19. Ahmadianfar, A., Heidari, A., Noshadian, S., Chen, H., Gandomi, A. H., “INFO: an efficient optimization algorithm based on weighted mean of vectors”, 2022, Expert Systems with Applications, 116516. doi: 10.1016/j.eswa.2022.116516.
  • 20. Rajendran, I., Vijayarangan, S., “Simulated annealing approach to the optimal design of automotive suspension systems”, 2007, Int. J. Vehicle Design, vol.43, pp.1-4.
Year 2023, Volume: 21 Issue: 2, 74 - 80, 24.11.2023
https://doi.org/10.56193/matim.1302774

Abstract

References

  • 1. Yap, Y. L., Toh, W., Giam, A., Yong, F. R., Chan, K. I., Tay, J. W. S., Ng, T. Y., “Topology optimization and 3D printing of micro-drone: Numerical design with experimental testing”, International Journal of Mechanical Sciences, 2023, vol.237, 107771.
  • 2. Rayed, A. M., Esakki, B., Ponnambalam, A., Banik, S. C., Aly, K., “Optimization of UAV structure and evaluation of vibrational and fatigue characteristics through simulation studies”, 2021, International Journal for Simulation and Multidisciplinary Design Optimization, Vol.12, 17.
  • 3. Palinkas, I., Pekez, J., Desnica, E., Rajic, A., Nedelcu, D., “Analysis and Optimization of UAV Frame Design for Manufacturing from Thermoplastic Materials on FDM 3D Printer”, 2021, Materiale Plastice, vol.58(4), pp.238-249.
  • 4. Nvss, S., Esakki, B., Yang, L. J., Udayagiri, C., Vepa, K. S., “Design and development of unibody quadcopter structure using optimization and additive manufacturing techniques”, 2022, Designs, vol.6(1), 8.
  • 5. Fang, H., Rais-Rohani, M., Liu, Z., “A comparative study of metamodeling methods for multiobjective crashworthiness optimization”, 2005, Computers and Structures, vol.83(25–26), pp.2121–2136.
  • 6. Kurtuluş, E., Yıldız, A.R., Sait, S.M., Bureerat, S., “A novel hybrid Harris hawks-simulated annealing algorithm and RBF-based metamodel for design optimization of highway guardrails”, 2020, Materials Testing, vol.62, pp.251-260.
  • 7. Gupta, S., Deep, K., “An efficient grey wolf optimizer with opposition-based learning and chaotic local search for integer and mixed-integer optimization problems”, 2019, Arabian Journal for Science and Engineering, vol.44, pp. 7277-7296.
  • 8. Gupta, S., Deep, K., “Optimal Coordination of Overcurrent Relays Using Improved Leadership-Based Grey Wolf Optimizer”, 2019, Arabian Journal for Science and Engineering, vol.45, pp.2081–2091.
  • 9. Pholdee, N., Bureerat, S.,Yildiz, A.R., “Hybrid real-code population-based incremental learning and differential evolution for many-objective optimisation of an automotive floor-frame”, 2017, International Journal of Vehicle Design, vol.73(1-3), pp. 20-53.
  • 10. Gupta, S., Deep, K., “Cauchy Grey Wolf Optimiser for continuous optimisation problems”, 2018, Journal of Experimental and Theoretical Artificial Intelligence, vol.30, pp.1051-1075.
  • 11. Gupta, S., Deep, K., “A novel hybrid sine cosine algorithm for global optimization and its application to train multilayer perceptrons”, 2019, Applied Intelligence, vol.50, pp.993-1026.
  • 12. Gupta, S., Deep, K., “A novel random walk grey wolf optimizer”, 2019, Swarm and Evolutionary Computation, vol.44, pp.101-112.
  • 13. Gupta, S., Deep, K., “A hybrid self-adaptive sine cosine algorithm with opposition based learning”, 2019, Expert Systems with Applications, vo.119, pp.210-230.
  • 14. Soh, H. J., Yoo, J. H., “Optimal shape design of a brake calliper for squeal noise reduction considering system instability”, 2010, Proceedings of the Institution of Mechanical Engineers, Part D: Journal of Automobile Engineering, vol.224(7), pp.909-925.
  • 15. Gupta, S., Deep, K., “Hybrid sine cosine artificial bee colony algorithm for global optimization and image segmentation”, 2019, Neural Computing and Applications, 1-23. doi:10.1007/s00521-019-04465-6
  • 16. Yildiz, B.S., Mehta, P., Sait, S.M., Panagant, N., Kumar, S., Yildiz, A.R., “A new hybrid artificial hummingbird-simulated annealing algorithm to solve constrained mechanical engineering problems”, 2022, Materials Testing, vol.64(7), pp.1043-1050.
  • 17. Karaboga, D., Basturk, B., “A powerful and efficient algorithm for numerical function optimization: artificial bee colony (ABC) algorithm”, 2007, Journal of Global Optimization, vol.39(3), pp.459–471.
  • 18. Mirjalili, S., Gandomi, A.H., Mirjalili, S.Z., Saremi, S., Faris, H., Mirjalili, S.M., “Multi verse Algorithm: A bio-inspired optimizer for engineering design problems”, 2017, Advances in Engineering Software, vol.114, pp.163-191.
  • 19. Ahmadianfar, A., Heidari, A., Noshadian, S., Chen, H., Gandomi, A. H., “INFO: an efficient optimization algorithm based on weighted mean of vectors”, 2022, Expert Systems with Applications, 116516. doi: 10.1016/j.eswa.2022.116516.
  • 20. Rajendran, I., Vijayarangan, S., “Simulated annealing approach to the optimal design of automotive suspension systems”, 2007, Int. J. Vehicle Design, vol.43, pp.1-4.

Details

Primary Language Turkish
Subjects Mechanical Engineering
Journal Section Araştırma, Geliştirme ve Uygulama Makaleleri
Authors

Betul YİLDİZ 0000-0002-7493-2068

Project Number FGA-2022-1252
Publication Date November 24, 2023
Submission Date May 25, 2023
Published in Issue Year 2023 Volume: 21 Issue: 2

Cite

Vancouver YİLDİZ B. Yeni Bir Hibrid Metasezgisel Algoritma İle Drone Kolunun Yapısal Optimizasyonu. MATİM. 2023;21(2):74-80.