Research Article
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Year 2023, Volume: 2 Issue: 2, 1 - 17, 30.12.2023

Abstract

References

  • Abd Elaziz, M., Elsheikh, A.H., Oliva, D., Abualigah, L., Lu, S., Ewees, A.A. 2021. Advanced metaheuristic techniques for mechanical design problems. Archives of Computational Methods in Engineering, 1–22.
  • Abdullah, E. 2022. A complete solution to exam scheduling problem: A case study. Journal of Scientific Reports-A, 049: 12–34.
  • Abualigah, L., Elaziz, M.A., Khasawneh, A.M., Alshinwan, M., Ibrahim, R.A., Al-Qaness, M.A., Mirjalili, S., Sumari, P., Gandomi, A.H. 2022. Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: A comprehensive survey, applications, comparative analysis, and results. Neural Computing and Applications, 1–30.
  • Adekanmbi, O., Green, P. 2015. Conceptual comparison of population based metaheuristics for engineering problems. The Scientific World Journal, 1-9.
  • Andersson, J. 2000. A survey of multiobjective optimization in engineering design. Department of Mechanical Engineering, Linktjping University. Sweden.
  • Belkourchia, Y., Azrar, L., Zeriab, E.S.M. 2019. A hybrid optimization algorithm for solving constrained engineering design problems. 2019 5th International Conference on Optimization and Applications (ICOA), 25-26 April, p: 1–7.
  • Braik, M., Sheta, A., Al-Hiary, H. 2021. A novel meta-heuristic search algorithm for solving optimization problems: Capuchin search algorithm. Neural Computing and Applications, 33: 2515–2547.
  • Carbas, S., Toktas, A., Ustun, D. 2021. Introduction and overview: Nature-inspired metaheuristic algorithms for engineering optimization applications. Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications. ISBN: 978-981-33-6773-9. Springer, Singapore. p: 1–9.
  • Cayiroglu, I., Elen, A. 2012. A heuristic optimization approach for a real-world university timetabling problem. Advances in Computer Science and Engineering, 9(2).
  • Jiao, R., Commuri, S., Panchal, J., Milisavljevic-Syed, J., Allen, J.K., Mistree, F., Schaefer, D. 2021. Design engineering in the age of industry 4.0. Journal of Mechanical Design, 143(7): 070801.
  • Lin, M.H., Tsai, J.F., Hu, N.Z., Chang, S.C. 2013. Design optimization of a speed reducer using deterministic techniques. Mathematical Problems in Engineering, 1-7.
  • Martins, J.R., Ning, A. 2021. Engineering design optimization. 1st ed. Cambridge University Press.
  • Meng, Z., Li, G., Wang, X., Sait, S. M., Yıldız, A.R. 2021. A comparative study of metaheuristic algorithms for reliability-based design optimization problems. Archives of Computational Methods in Engineering, 28: 1853–1869.
  • Ragsdell, K.M., Phillips, D.T. 1976. Optimal design of a class of welded structures using geometric programming.
  • Rather, S.A., Bala, P.S. 2020. Swarm-based chaotic gravitational search algorithm for solving mechanical engineering design problems. World Journal of Engineering, 17(1): 97–114.
  • Salcedo-Sanz, S. 2016. Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures. Physics Reports, 655: 1–70.
  • Savsani, P., Savsani, V. 2016. Passing vehicle search (PVS): A novel metaheuristic algorithm. Applied Mathematical Modelling, 40(5–6): 3951–3978.
  • Sheikhi Azqandi, M., Delavar, M., Arjmand, M. 2020. An enhanced time evolutionary optimization for solving engineering design problems. Engineering with Computers, 36(2): 763–781.
  • Talatahari, S., Azizi, M. 2020. Optimization of constrained mathematical and engineering design problems using chaos game optimization. Computers & Industrial Engineering, 145: 106560.
  • Wong, W.K., Ming, C.I. 2019. A review on metaheuristic algorithms: Recent trends, benchmarking and applications. 2019 7th International Conference on Smart Computing & Communications (ICSCC), 28-30 June, p:1–5.
  • Yao, J., Sha, Y., Chen, Y., Zhao, X. 2022. A Novel ensemble of arithmetic optimization algorithm and Harris hawks optimization for solving industrial engineering optimization problems. Machines, 10(8): 602.
  • Zailani, Z.A., Zaibi, N.M., Hamidon, R., Harun, A., Bahari, M.S., Zakaria, S. 2021. Improvement on the surface quality in machining of aluminum alloy involving boron nitride nanoparticles. Intelligent Manufacturing and Mechatronics. ISBN: 978-981-16-0866-7. Springer, Singapore. p: 351–363.
  • Zuo, W., Zhao, C., Zhou, L., Guo, G. 2019. Comparison of gradient and nongradient algorithms in the structural optimization course. International Journal of Mechanical Engineering Education, 47(3): 275–290.

Solving Mechanical Engineering Problems by Metaheuristic Methods

Year 2023, Volume: 2 Issue: 2, 1 - 17, 30.12.2023

Abstract

The goal of optimization is to create the "best" design possible given a set of prioritized conditions or constraints. These include increasing productivity, power, reliability, longevity, efficiency, and utilization. Because of their simplicity and speed in finding solutions, metaheuristic algorithms, one of the optimization techniques, have grown in importance in engineering design in recent years. This has resulted in the widespread use of metaheuristics and a growing proclivity to create new algorithms. In this study, a research was conducted on addressing real-world problems (Robot Gripper Problem, Pressure Vessel Design Problem, Rolling Element Bearing Problem, Step-Cone Pulley Problem, Tension Compression Spring Design Problem, Three-Bar Truss Beam Design Problem, Weight Minimization of Speed Reducer Problem and Welded Beam Design Problem) in the field of mechanical engineering with metaheuristic algorithms (Ant Colony Optimization, Artificial Bee Colony, Salp Swarm Algorithm and Sine Cosine Algorithm) and performing performance analyzes of these algorithms. In the experimental studies, four different scenarios were progressively determined according to various number of iterations and population parameters. Consequently, it can be confidently asserted that ACOR not only produces superior solutions but also boasts an ideal running time for efficiently solving real-world problems.

References

  • Abd Elaziz, M., Elsheikh, A.H., Oliva, D., Abualigah, L., Lu, S., Ewees, A.A. 2021. Advanced metaheuristic techniques for mechanical design problems. Archives of Computational Methods in Engineering, 1–22.
  • Abdullah, E. 2022. A complete solution to exam scheduling problem: A case study. Journal of Scientific Reports-A, 049: 12–34.
  • Abualigah, L., Elaziz, M.A., Khasawneh, A.M., Alshinwan, M., Ibrahim, R.A., Al-Qaness, M.A., Mirjalili, S., Sumari, P., Gandomi, A.H. 2022. Meta-heuristic optimization algorithms for solving real-world mechanical engineering design problems: A comprehensive survey, applications, comparative analysis, and results. Neural Computing and Applications, 1–30.
  • Adekanmbi, O., Green, P. 2015. Conceptual comparison of population based metaheuristics for engineering problems. The Scientific World Journal, 1-9.
  • Andersson, J. 2000. A survey of multiobjective optimization in engineering design. Department of Mechanical Engineering, Linktjping University. Sweden.
  • Belkourchia, Y., Azrar, L., Zeriab, E.S.M. 2019. A hybrid optimization algorithm for solving constrained engineering design problems. 2019 5th International Conference on Optimization and Applications (ICOA), 25-26 April, p: 1–7.
  • Braik, M., Sheta, A., Al-Hiary, H. 2021. A novel meta-heuristic search algorithm for solving optimization problems: Capuchin search algorithm. Neural Computing and Applications, 33: 2515–2547.
  • Carbas, S., Toktas, A., Ustun, D. 2021. Introduction and overview: Nature-inspired metaheuristic algorithms for engineering optimization applications. Nature-Inspired Metaheuristic Algorithms for Engineering Optimization Applications. ISBN: 978-981-33-6773-9. Springer, Singapore. p: 1–9.
  • Cayiroglu, I., Elen, A. 2012. A heuristic optimization approach for a real-world university timetabling problem. Advances in Computer Science and Engineering, 9(2).
  • Jiao, R., Commuri, S., Panchal, J., Milisavljevic-Syed, J., Allen, J.K., Mistree, F., Schaefer, D. 2021. Design engineering in the age of industry 4.0. Journal of Mechanical Design, 143(7): 070801.
  • Lin, M.H., Tsai, J.F., Hu, N.Z., Chang, S.C. 2013. Design optimization of a speed reducer using deterministic techniques. Mathematical Problems in Engineering, 1-7.
  • Martins, J.R., Ning, A. 2021. Engineering design optimization. 1st ed. Cambridge University Press.
  • Meng, Z., Li, G., Wang, X., Sait, S. M., Yıldız, A.R. 2021. A comparative study of metaheuristic algorithms for reliability-based design optimization problems. Archives of Computational Methods in Engineering, 28: 1853–1869.
  • Ragsdell, K.M., Phillips, D.T. 1976. Optimal design of a class of welded structures using geometric programming.
  • Rather, S.A., Bala, P.S. 2020. Swarm-based chaotic gravitational search algorithm for solving mechanical engineering design problems. World Journal of Engineering, 17(1): 97–114.
  • Salcedo-Sanz, S. 2016. Modern meta-heuristics based on nonlinear physics processes: A review of models and design procedures. Physics Reports, 655: 1–70.
  • Savsani, P., Savsani, V. 2016. Passing vehicle search (PVS): A novel metaheuristic algorithm. Applied Mathematical Modelling, 40(5–6): 3951–3978.
  • Sheikhi Azqandi, M., Delavar, M., Arjmand, M. 2020. An enhanced time evolutionary optimization for solving engineering design problems. Engineering with Computers, 36(2): 763–781.
  • Talatahari, S., Azizi, M. 2020. Optimization of constrained mathematical and engineering design problems using chaos game optimization. Computers & Industrial Engineering, 145: 106560.
  • Wong, W.K., Ming, C.I. 2019. A review on metaheuristic algorithms: Recent trends, benchmarking and applications. 2019 7th International Conference on Smart Computing & Communications (ICSCC), 28-30 June, p:1–5.
  • Yao, J., Sha, Y., Chen, Y., Zhao, X. 2022. A Novel ensemble of arithmetic optimization algorithm and Harris hawks optimization for solving industrial engineering optimization problems. Machines, 10(8): 602.
  • Zailani, Z.A., Zaibi, N.M., Hamidon, R., Harun, A., Bahari, M.S., Zakaria, S. 2021. Improvement on the surface quality in machining of aluminum alloy involving boron nitride nanoparticles. Intelligent Manufacturing and Mechatronics. ISBN: 978-981-16-0866-7. Springer, Singapore. p: 351–363.
  • Zuo, W., Zhao, C., Zhou, L., Guo, G. 2019. Comparison of gradient and nongradient algorithms in the structural optimization course. International Journal of Mechanical Engineering Education, 47(3): 275–290.
There are 23 citations in total.

Details

Primary Language English
Subjects Computer Software
Journal Section Research Articles
Authors

Samet Panda 0000-0002-1026-7759

Serhat Kılıçarslan 0000-0001-9483-4425

Abdullah Elen 0000-0003-1644-0476

Publication Date December 30, 2023
Submission Date December 20, 2023
Acceptance Date December 27, 2023
Published in Issue Year 2023 Volume: 2 Issue: 2

Cite

APA Panda, S., Kılıçarslan, S., & Elen, A. (2023). Solving Mechanical Engineering Problems by Metaheuristic Methods. Uluslararası Sivas Bilim Ve Teknoloji Üniversitesi Dergisi, 2(2), 1-17.