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Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems

Yıl 2025, Cilt: 6 Sayı: 1, 150 - 169, 19.06.2025

Nermin Ozcan

https://doi.org/10.55546/jmm.1660142

Öz

The intricacy of decision variables, multiple objectives, and nonlinear restrictions make it difficult to find suitable solutions for mechanical design problems. An alternative approach to these difficult challenges, the Grey Wolf Optimizer (GWO) is recognized for its ease of use, flexibility, scalability, and unique balance between exploration and exploitation. Like every stochastic approach, GWO has drawbacks, though, and numerous enhanced variants have been put up to overcome them. The GWO algorithm and its variants are examined in this investigation. It conducts an experimental comparison of the original approach and its two variations. It examines how the approaches behave with various combinations of parameters. Five mechanical design problems are used to test the algorithms' effectiveness utilizing statistical analysis and search performance. In the literature, the performance of alternative approaches is also contrasted with the ideal outcomes.

Anahtar Kelimeler

Grey wolf optimizer Engineering problem Mechanical design Meta-heuristic algorithm Optimization

Teşekkür

This study did not benefit from any support.

Kaynakça

  • Abdollahzadeh B., Gharehchopogh F. S., Mirjalili S., African Vultures Optimization Algorithm: A New Nature-Inspired Metaheuristic Algorithm for Global Optimization Problems, Computers and Industrial Engineering 158(5), 107408, 2021.
  • Altay O., Varol E., A Novel Hybrid Multilayer Perceptron Neural Network with Improved Grey Wolf Optimizer, Neural Computing and Applications, 35(1), 529–556, 2023.
  • Ayğahoğlu M. E., Gümüş M. S., Çakan, A., Kalyoncu M., Dimension Optimization of Polycentric Knee Mechanism using the Bees Algorithm And Genetic Algorithm, Journal of Materials and Mechatronics: A 4(1), 318–332, 2023.
  • Bayzidi H., Talatahari S., Saraee M., Lamarche, C. P., Social Network Search for Solving Engineering Optimization Problems, Computational Intelligence and Neuroscience 548639, 2021.
  • Çetinkaya M. B., Taşkıran K., Meta-Sezgisel Algoritmalara Dayalı Retinal Damar Bölütleme, Journal of Materials and Mechatronics: A 3(1), 79–90, 2022.
  • Coban M., Saka M., Directly Power System Harmonics Estimation using Equilibrium Optimizer, Electric Power Systems Research, 234(110565), 2024.
  • Cui D., Wang G., Lu Y., Sun K., Reliability Design and Optimization of The Planetary Gear by a GA Based on the DEM and Kriging Model, Reliability Engineering & System Safety 203,107074, 2020.
  • Das B., Mukherjee V., Das D., Student Psychology based Optimization Algorithm: A New Population based Optimization Algorithm for Solving Optimization Problems, Advances in Engineering Software 146(3), 102804, 2020.
  • Debnath S., Debbarma S., Nama S., Saha A. K., Dhar R., Yildiz A. R., Gandomi A. H., Centroid Opposition-Based Backtracking Search Algorithm For Global Optimization And Engineering Problems, Advances in Engineering Software 198, 103784, 2024.
  • Eberhart R., Kennedy J., New Optimizer using Particle Swarm Theory, Proceedings of the International Symposium on Micro Machine and Human Science 39–43, 1995.
  • Eke I., Saka M., Gozde H., Arya Y., Taplamacioglu M. C., Heuristic Optimization based Dynamic Weighted State Feedback Approach for 2DOF PI-Controller in Automatic Voltage Regulator, Engineering Science and Technology, an International Journal 24(4), 899–910, 2021.
  • Emary E., Zawbaa H. M., Hassanien A. E., Binary Grey Wolf Optimization Approaches for Feature Selection, Neurocomputing 172, 371–381, 2016.
  • Ezugwu A. E., Agushaka J. O., Abualigah L., Mirjalili S., Gandomi A. H., Prairie Dog Optimization Algorithm, Neural Computing and Applications 34(22), 2022.
  • Faramarzi A., Heidarinejad M., Stephens B., Mirjalili S., Equilibrium Optimizer: A Novel Optimization Algorithm, Knowledge-Based Systems 191, 105190, 2020.
  • Faris H., Aljarah I., Al-Betar M. A., Mirjalili S., Grey Wolf Optimizer: A Review ff Recent Variants and Applications, Neural Computing and Applications 30(2), 413–435, 2018.
  • Gezici H., Improved Tuna Swarm Optimization Algorithm for Engineering Design Problems, Journal of Materials and Mechatronics: A 4(2), 424–445, 2023.
  • Gupta S., Abderazek H., Yıldız B. S., Yildiz A. R., Mirjalili S., Sait, S. M., Comparison of Metaheuristic Optimization Algorithms for Solving Constrained Mechanical Design Optimization Problems, Expert Systems with Applications 183, 2021.
  • Gupta S., Deep K., A Novel Random Walk Grey Wolf Optimizer, Swarm and Evolutionary Computation 44, 101–112, 2019.
  • Gürkan Kuntalp D., Özcan N., Düzyel O., Kababulut F. Y., Kuntalp M., A Comparative Study of Metaheuristic Feature Selection Algorithms for Respiratory Disease Classification, Diagnostics 14(19), 2244, 2024.
  • Hamza F., Abderazek H., Lakhdar S., Ferhat D., Yıldız A. R., Optimum Design of Cam-Roller Follower Mechanism using a New Evolutionary Algorithm, The International Journal of Advanced Manufacturing Technology 99(5), 1267–1282, 2018.
  • Heidari A. A., Mirjalili S., Faris H., Aljarah I., Mafarja M., Chen H., Harris Hawks Optimization: Algorithm and Applications, Future Generation Computer Systems 97, 849–872, 2019.
  • Holland J. H., Genetic Algorithms, Scientific American 267(1), 66–72, 1992.
  • Jahangiri M., Hadianfard M. A., Najafgholipour M. A., Jahangiri M., Gerami M. R., Interactive Autodidactic School: A New Metaheuristic Optimization Algorithm for Solving Mathematical and Structural Design Optimization Problems, Computers & Structures 235, 2020.
  • Jayapriya J., Arock M., A Parallel GWO Technique for Aligning Multiple Molecular Sequences, International Conference on Advances in Computing, Communications and Informatics (ICACCI), India, 210–215, 2015.
  • Kababulut F. Y., Gürkan Kuntalp D., Düzyel O., Özcan N., Kuntalp M., A New Shapley-Based Feature Selection Method in a Clinical Decision Support System for the Identification of Lung Diseases, Diagnostics 13(23), 3558, 2023.
  • Kamboj V. K., A Novel Hybrid PSO–GWO Approach for Unit Commitment Problem, Neural Computing and Applications 27(6), 1643–1655, 2016.
  • Kaveh A., Zakian P., Improved GWO Algorithm for Optimal Design of Truss Structures, Engineering with Computers 34(4), 685–707, 2018.
  • Khairuzzaman A. K. M., Chaudhury S., Multilevel Thresholding using Grey Wolf Optimizer for Image Segmentation, Expert Systems with Applications 86, 64–76, 2017.
  • Kishor A., Singh P. K., Empirical Study of Grey Wolf Optimizer, Proceedings of Fifth International Conference on Soft Computing for Problem Solving, Singapore, 1037–1049, 2016.
  • Lee S. W., Haider A., Rahmani A. M., Arasteh B., Gharehchopogh F. S., Tang S., Liu Z., Aurangzeb K., Hosseinzadeh M., A Survey of Beluga Whale Optimization and Its Variants: Statistical Analysis, Advances, and Structural Reviewing, Computer Science Review 57, 2025.
  • Li G., Zhang T., Tsai C. Y., Yao L., Lu Y., Tang J., Review of the Metaheuristic Algorithms in Applications: Visual Analysis based on Bibliometrics, Expert Systems with Applications 255, 2024.
  • Li S. X., Wang J. S., Dynamic Modeling of Steam Condenser and Design of Pi Controller based on Grey Wolf Optimizer, Mathematical Problems in Engineering 120975, 2015.
  • Luo Q., Zhang S., Li Z., Zhou Y., A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm, Algorithms 9(1), 2016.
  • Malik M. R. S., Mohideen E. R., Ali L., Weighted Distance Grey Wolf Optimizer for Global Optimization Problems, IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), India, 1–6, 2015.
  • Millo F., Arya P. Mallamo F., Optimization of Automotive Diesel Engine Calibration using Genetic Algorithm Techniques, Energy 158, 807–819, 2018.
  • Mirjalili S., Saremi S., Mirjalili S. M., Coelho L. S., Multi-Objective Grey Wolf Optimizer: A Novel Algorithm for Multi-Criterion Optimization, Expert Systems with Applications 47, 106–119, 2016.
  • Mirjalili S., Lewis A., The Whale Optimization Algorithm, Advances in Engineering Software 95, 51–67, 2016.
  • Mirjalili S., Mirjalili S. M., Lewis A., Grey Wolf Optimizer, Advances in Engineering Software 69, 46–61, 2014.
  • Mirjalili S., Gandomi A. H., Mirjalili S. Z., Saremi S., Faris H., Mirjalili S. M., Salp Swarm Algorithm: A Bio-Inspired Optimizer for Engineering Design Problems, Advances in Engineering Software 114, 163–191, 2017.
  • Mittal N., Singh U., Sohi, B. S., Modified Grey Wolf Optimizer for Global Engineering Optimization, Applied Computational Intelligence and Soft Computing, 2016(1), 2016.
  • Özcan N., Kuntalp M., Determining Best HRV Indices for PAF Screening using Genetic Algorithm, 10th International Conference on Electrical and Electronics Engineering (ELECO), Bursa, 2018.
  • Özcan N., Utku S. Berber T., Artificial Circulation System Algorithm: A Novel Bio-Inspired Algorithm, CMES - Computer Modeling in Engineering and Sciences 142(1), 635–663, 2025.
  • Ransegnola T., Zhao X., Vacca A., A Comparison of Helical and Spur External Gear Machines for Fluid Power Applications: Design And Optimization, Mechanism and Machine Theory 142, 2019.
  • Rodan A., Al-Tamimi A. K., Al-Alnemer L., Mirjalili S., Tino P., Enzyme Action Optimizer: A Novel Bio-Inspired Optimization Algorithm, The Journal of Supercomputing 81(5), 686, 2025.
  • Rodríguez L., Castillo O., Soria J., Melin P., Valdez F., Gonzalez C. I., Martinez G. E., Soto J., A Fuzzy Hierarchical Operator in the Grey Wolf Optimizer Algorithm, Applied Soft Computing 57, 315–328, 2017.
  • Saka M., Novel HVsaGwo Algorithm for Non-Linear Dynamic Weighted State Feedback With 1DOF-PID based Controllers in AVR, Engineering Science and Technology, an International Journal 59, 2024.
  • Saremi S., Mirjalili S., Lewis, A., Grasshopper Optimisation Algorithm: Theory and Application, Advances in Engineering Software 105, 30–47, 2017.
  • Socha K., Dorigo M., Ant Colony Optimization for Continuous Domains, European Journal of Operational Research 185(3), 1155–1173, 2008.
  • Song X., Tang L., Zhao S., Zhang X., Li L., Huang J., Cai W., Grey Wolf Optimizer for Parameter Estimation in Surface Waves, Soil Dynamics and Earthquake Engineering 75, 147–157, 2015.
  • Storn R., Price K., Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, Australasian Plant Pathology 38(3), 284–287, 2009.
  • Sulaiman M. H., Mustaffa Z., Mohamed M. R., Aliman O., Using the Gray Wolf Optimizer for Solving Optimal Reactive Power Dispatch Problem, Applied Soft Computing 32, 286–292, 2015.
  • Sun G., Tian J., Liu T., Yan X., Huang X., Crashworthiness Optimization of Automotive Parts with Tailor Rolled Blank, Engineering Structures 169, 201–215, 2018.
  • Van Thieu N, 2023., ENOPPY: A Python Library For Engineering Optimization Problems, https://github.com/thieu1995/enoppy (Accessed: 23.03.2025).
  • Van Thieu N., Mirjalili S., MEALPY: An Open-Source Library for Latest Meta-Heuristic Algorithms in Python, Journal of Systems Architecture 102871, 2023.
  • Wang R. B., Hu R. B., Geng F. D., Xu L., Chu S. C., Pan J. S., Meng Z. Y., Mirjalili S., The Animated Oat Optimization Algorithm: A Nature-Inspired Metaheuristic for Engineering Optimization and A Case Study On Wireless Sensor Networks, Knowledge-Based Systems, 113589, 2025.
  • Wolpert D. H., Macready W. G., No Free Lunch Theorems for Optimization, IEEE Transactions on Evolutionary Computation 1(1), 67–82, 1997.
  • Xu Y., Zhong R., Cao Y., Zhang C., Yu J., Symbiotic Mechanism-based Honey Badger Algorithm for Continuous Optimization, Cluster Computing 28(2), 2024.
  • Xu Y., Zhong R., Zhang C., Yu J., Crested Ibis Algorithm and Its Application in Human-Powered Aircraft Design, Knowledge-Based Systems 310, 2025.
  • Yang B., Zhang X., Yu T., Shu H., Fang Z., Grouped Grey Wolf Optimizer for Maximum Power Point Tracking of Doubly-Fed Induction Generator based Wind Turbine, Energy Conversion and Management 133, 427–443, 2017.
  • Yapici H., Cetinkaya N., A New Meta-Heuristic Optimizer: Pathfinder Algorithm, Applied Soft Computing Journal 78, 545–568, 2019.
  • Zhang S., Zhou Y., Li Z., Pan W., Grey Wolf Optimizer for Unmanned Combat Aerial Vehicle Path Planning, Advances in Engineering Software 99, 121–136, 2016.
  • Zhang S., Zhou Y., Grey Wolf Optimizer based on Powell Local Optimization Method for Clustering Analysis, Discrete Dynamics in Nature and Society 481360, 2015.
  • Zhong R., Yu J., Zhang C., Munetomo M., SRIME: A Strengthened RIME with Latin Hypercube Sampling and Embedded Distance-based Selection for Engineering Optimization Problems, Neural Computing and Applications 36(12), 2024.
  • Zhong R., Hussien A. G., Yu J., Munetomo M., LLMOA: A Novel Large Language Model Assisted Hyper-Heuristic Optimization Algorithm, Advanced Engineering Informatics 64, 2025.
  • Zhong R., Wang Z., Hussien A. G., Houssein E. H., Al-Shourbaji I., Elseify M. A., Yu J., Success History Adaptive Competitive Swarm Optimizer With Linear Population Reduction: Performance Benchmarking and Application in Eye Disease Detection, Computers in Biology and Medicine 186, 2025.
  • Zhong R., Zhang C., Yu J., Chaotic Vegetation Evolution: Leveraging Multiple Seeding Strategies and a Mutation Module for Global Optimization Problems, Evolutionary Intelligence 17(4), 2024.
  • Zhong R., Zhang C., Yu J., Cooperative Coati Optimization Algorithm with Transfer Functions for Feature Selection and Knapsack Problems, Knowledge and Information Systems, 66(11), 2024.
  • Zhou J., Zhu W., Zheng Y., Li C., Precise Equivalent Model of Small Hydro Generator Cluster and Its Parameter Identification using Improved Grey Wolf Optimiser, IET Generation, Transmission and Distribution 10(9), 2016.

Mekanik Optimizasyon Problemlerinin Çözümü için GWO ve Varyantlarının Kapsamlı Karşılaştırmalı Analizi

Yıl 2025, Cilt: 6 Sayı: 1, 150 - 169, 19.06.2025

Nermin Ozcan

https://doi.org/10.55546/jmm.1660142

Öz

Karar değişkenlerinin karmaşıklığı, çoklu hedefler ve doğrusal olmayan kısıtlamalar, mekanik tasarım problemleri için uygun çözümler bulmayı zorlaştırmaktadır. Bu zorlu problemlere alternatif bir yaklaşım olan Gri Kurt Optimizasyonu (GKO), kullanım kolaylığı, esnekliği, ölçeklenebilirliği ve keşif ile sömürü arasındaki benzersiz dengesiyle tanınmaktadır. Her stokastik yaklaşım gibi, GKO'nun da dezavantajları vardır ve bunların üstesinden gelmek için çok sayıda geliştirilmiş varyant ortaya konmuştur. Bu araştırmada GKO algoritması ve varyantları incelenmiştir. Orijinal yaklaşım ve iki varyasyonunun deneysel bir karşılaştırması yapılmaktadır. Yaklaşımların çeşitli parametre kombinasyonlarının performans üzerindeki etkisi incelenmektedir. İstatistiksel analiz ve arama performansı kullanılarak algoritmaların etkinliğini test etmek için beş mekanik tasarım problemi kullanılmıştır. Literatürde, alternatif yaklaşımların performansı da ideal sonuçlarla karşılaştırılmaktadır.

Anahtar Kelimeler

Gri kurt optimizasyonu Mühendislik problemi Mekanik tasarım Meta-sezgisel algoritma

Kaynakça

  • Abdollahzadeh B., Gharehchopogh F. S., Mirjalili S., African Vultures Optimization Algorithm: A New Nature-Inspired Metaheuristic Algorithm for Global Optimization Problems, Computers and Industrial Engineering 158(5), 107408, 2021.
  • Altay O., Varol E., A Novel Hybrid Multilayer Perceptron Neural Network with Improved Grey Wolf Optimizer, Neural Computing and Applications, 35(1), 529–556, 2023.
  • Ayğahoğlu M. E., Gümüş M. S., Çakan, A., Kalyoncu M., Dimension Optimization of Polycentric Knee Mechanism using the Bees Algorithm And Genetic Algorithm, Journal of Materials and Mechatronics: A 4(1), 318–332, 2023.
  • Bayzidi H., Talatahari S., Saraee M., Lamarche, C. P., Social Network Search for Solving Engineering Optimization Problems, Computational Intelligence and Neuroscience 548639, 2021.
  • Çetinkaya M. B., Taşkıran K., Meta-Sezgisel Algoritmalara Dayalı Retinal Damar Bölütleme, Journal of Materials and Mechatronics: A 3(1), 79–90, 2022.
  • Coban M., Saka M., Directly Power System Harmonics Estimation using Equilibrium Optimizer, Electric Power Systems Research, 234(110565), 2024.
  • Cui D., Wang G., Lu Y., Sun K., Reliability Design and Optimization of The Planetary Gear by a GA Based on the DEM and Kriging Model, Reliability Engineering & System Safety 203,107074, 2020.
  • Das B., Mukherjee V., Das D., Student Psychology based Optimization Algorithm: A New Population based Optimization Algorithm for Solving Optimization Problems, Advances in Engineering Software 146(3), 102804, 2020.
  • Debnath S., Debbarma S., Nama S., Saha A. K., Dhar R., Yildiz A. R., Gandomi A. H., Centroid Opposition-Based Backtracking Search Algorithm For Global Optimization And Engineering Problems, Advances in Engineering Software 198, 103784, 2024.
  • Eberhart R., Kennedy J., New Optimizer using Particle Swarm Theory, Proceedings of the International Symposium on Micro Machine and Human Science 39–43, 1995.
  • Eke I., Saka M., Gozde H., Arya Y., Taplamacioglu M. C., Heuristic Optimization based Dynamic Weighted State Feedback Approach for 2DOF PI-Controller in Automatic Voltage Regulator, Engineering Science and Technology, an International Journal 24(4), 899–910, 2021.
  • Emary E., Zawbaa H. M., Hassanien A. E., Binary Grey Wolf Optimization Approaches for Feature Selection, Neurocomputing 172, 371–381, 2016.
  • Ezugwu A. E., Agushaka J. O., Abualigah L., Mirjalili S., Gandomi A. H., Prairie Dog Optimization Algorithm, Neural Computing and Applications 34(22), 2022.
  • Faramarzi A., Heidarinejad M., Stephens B., Mirjalili S., Equilibrium Optimizer: A Novel Optimization Algorithm, Knowledge-Based Systems 191, 105190, 2020.
  • Faris H., Aljarah I., Al-Betar M. A., Mirjalili S., Grey Wolf Optimizer: A Review ff Recent Variants and Applications, Neural Computing and Applications 30(2), 413–435, 2018.
  • Gezici H., Improved Tuna Swarm Optimization Algorithm for Engineering Design Problems, Journal of Materials and Mechatronics: A 4(2), 424–445, 2023.
  • Gupta S., Abderazek H., Yıldız B. S., Yildiz A. R., Mirjalili S., Sait, S. M., Comparison of Metaheuristic Optimization Algorithms for Solving Constrained Mechanical Design Optimization Problems, Expert Systems with Applications 183, 2021.
  • Gupta S., Deep K., A Novel Random Walk Grey Wolf Optimizer, Swarm and Evolutionary Computation 44, 101–112, 2019.
  • Gürkan Kuntalp D., Özcan N., Düzyel O., Kababulut F. Y., Kuntalp M., A Comparative Study of Metaheuristic Feature Selection Algorithms for Respiratory Disease Classification, Diagnostics 14(19), 2244, 2024.
  • Hamza F., Abderazek H., Lakhdar S., Ferhat D., Yıldız A. R., Optimum Design of Cam-Roller Follower Mechanism using a New Evolutionary Algorithm, The International Journal of Advanced Manufacturing Technology 99(5), 1267–1282, 2018.
  • Heidari A. A., Mirjalili S., Faris H., Aljarah I., Mafarja M., Chen H., Harris Hawks Optimization: Algorithm and Applications, Future Generation Computer Systems 97, 849–872, 2019.
  • Holland J. H., Genetic Algorithms, Scientific American 267(1), 66–72, 1992.
  • Jahangiri M., Hadianfard M. A., Najafgholipour M. A., Jahangiri M., Gerami M. R., Interactive Autodidactic School: A New Metaheuristic Optimization Algorithm for Solving Mathematical and Structural Design Optimization Problems, Computers & Structures 235, 2020.
  • Jayapriya J., Arock M., A Parallel GWO Technique for Aligning Multiple Molecular Sequences, International Conference on Advances in Computing, Communications and Informatics (ICACCI), India, 210–215, 2015.
  • Kababulut F. Y., Gürkan Kuntalp D., Düzyel O., Özcan N., Kuntalp M., A New Shapley-Based Feature Selection Method in a Clinical Decision Support System for the Identification of Lung Diseases, Diagnostics 13(23), 3558, 2023.
  • Kamboj V. K., A Novel Hybrid PSO–GWO Approach for Unit Commitment Problem, Neural Computing and Applications 27(6), 1643–1655, 2016.
  • Kaveh A., Zakian P., Improved GWO Algorithm for Optimal Design of Truss Structures, Engineering with Computers 34(4), 685–707, 2018.
  • Khairuzzaman A. K. M., Chaudhury S., Multilevel Thresholding using Grey Wolf Optimizer for Image Segmentation, Expert Systems with Applications 86, 64–76, 2017.
  • Kishor A., Singh P. K., Empirical Study of Grey Wolf Optimizer, Proceedings of Fifth International Conference on Soft Computing for Problem Solving, Singapore, 1037–1049, 2016.
  • Lee S. W., Haider A., Rahmani A. M., Arasteh B., Gharehchopogh F. S., Tang S., Liu Z., Aurangzeb K., Hosseinzadeh M., A Survey of Beluga Whale Optimization and Its Variants: Statistical Analysis, Advances, and Structural Reviewing, Computer Science Review 57, 2025.
  • Li G., Zhang T., Tsai C. Y., Yao L., Lu Y., Tang J., Review of the Metaheuristic Algorithms in Applications: Visual Analysis based on Bibliometrics, Expert Systems with Applications 255, 2024.
  • Li S. X., Wang J. S., Dynamic Modeling of Steam Condenser and Design of Pi Controller based on Grey Wolf Optimizer, Mathematical Problems in Engineering 120975, 2015.
  • Luo Q., Zhang S., Li Z., Zhou Y., A Novel Complex-Valued Encoding Grey Wolf Optimization Algorithm, Algorithms 9(1), 2016.
  • Malik M. R. S., Mohideen E. R., Ali L., Weighted Distance Grey Wolf Optimizer for Global Optimization Problems, IEEE International Conference on Computational Intelligence and Computing Research (ICCIC), India, 1–6, 2015.
  • Millo F., Arya P. Mallamo F., Optimization of Automotive Diesel Engine Calibration using Genetic Algorithm Techniques, Energy 158, 807–819, 2018.
  • Mirjalili S., Saremi S., Mirjalili S. M., Coelho L. S., Multi-Objective Grey Wolf Optimizer: A Novel Algorithm for Multi-Criterion Optimization, Expert Systems with Applications 47, 106–119, 2016.
  • Mirjalili S., Lewis A., The Whale Optimization Algorithm, Advances in Engineering Software 95, 51–67, 2016.
  • Mirjalili S., Mirjalili S. M., Lewis A., Grey Wolf Optimizer, Advances in Engineering Software 69, 46–61, 2014.
  • Mirjalili S., Gandomi A. H., Mirjalili S. Z., Saremi S., Faris H., Mirjalili S. M., Salp Swarm Algorithm: A Bio-Inspired Optimizer for Engineering Design Problems, Advances in Engineering Software 114, 163–191, 2017.
  • Mittal N., Singh U., Sohi, B. S., Modified Grey Wolf Optimizer for Global Engineering Optimization, Applied Computational Intelligence and Soft Computing, 2016(1), 2016.
  • Özcan N., Kuntalp M., Determining Best HRV Indices for PAF Screening using Genetic Algorithm, 10th International Conference on Electrical and Electronics Engineering (ELECO), Bursa, 2018.
  • Özcan N., Utku S. Berber T., Artificial Circulation System Algorithm: A Novel Bio-Inspired Algorithm, CMES - Computer Modeling in Engineering and Sciences 142(1), 635–663, 2025.
  • Ransegnola T., Zhao X., Vacca A., A Comparison of Helical and Spur External Gear Machines for Fluid Power Applications: Design And Optimization, Mechanism and Machine Theory 142, 2019.
  • Rodan A., Al-Tamimi A. K., Al-Alnemer L., Mirjalili S., Tino P., Enzyme Action Optimizer: A Novel Bio-Inspired Optimization Algorithm, The Journal of Supercomputing 81(5), 686, 2025.
  • Rodríguez L., Castillo O., Soria J., Melin P., Valdez F., Gonzalez C. I., Martinez G. E., Soto J., A Fuzzy Hierarchical Operator in the Grey Wolf Optimizer Algorithm, Applied Soft Computing 57, 315–328, 2017.
  • Saka M., Novel HVsaGwo Algorithm for Non-Linear Dynamic Weighted State Feedback With 1DOF-PID based Controllers in AVR, Engineering Science and Technology, an International Journal 59, 2024.
  • Saremi S., Mirjalili S., Lewis, A., Grasshopper Optimisation Algorithm: Theory and Application, Advances in Engineering Software 105, 30–47, 2017.
  • Socha K., Dorigo M., Ant Colony Optimization for Continuous Domains, European Journal of Operational Research 185(3), 1155–1173, 2008.
  • Song X., Tang L., Zhao S., Zhang X., Li L., Huang J., Cai W., Grey Wolf Optimizer for Parameter Estimation in Surface Waves, Soil Dynamics and Earthquake Engineering 75, 147–157, 2015.
  • Storn R., Price K., Differential Evolution - A Simple and Efficient Heuristic for Global Optimization over Continuous Spaces, Australasian Plant Pathology 38(3), 284–287, 2009.
  • Sulaiman M. H., Mustaffa Z., Mohamed M. R., Aliman O., Using the Gray Wolf Optimizer for Solving Optimal Reactive Power Dispatch Problem, Applied Soft Computing 32, 286–292, 2015.
  • Sun G., Tian J., Liu T., Yan X., Huang X., Crashworthiness Optimization of Automotive Parts with Tailor Rolled Blank, Engineering Structures 169, 201–215, 2018.
  • Van Thieu N, 2023., ENOPPY: A Python Library For Engineering Optimization Problems, https://github.com/thieu1995/enoppy (Accessed: 23.03.2025).
  • Van Thieu N., Mirjalili S., MEALPY: An Open-Source Library for Latest Meta-Heuristic Algorithms in Python, Journal of Systems Architecture 102871, 2023.
  • Wang R. B., Hu R. B., Geng F. D., Xu L., Chu S. C., Pan J. S., Meng Z. Y., Mirjalili S., The Animated Oat Optimization Algorithm: A Nature-Inspired Metaheuristic for Engineering Optimization and A Case Study On Wireless Sensor Networks, Knowledge-Based Systems, 113589, 2025.
  • Wolpert D. H., Macready W. G., No Free Lunch Theorems for Optimization, IEEE Transactions on Evolutionary Computation 1(1), 67–82, 1997.
  • Xu Y., Zhong R., Cao Y., Zhang C., Yu J., Symbiotic Mechanism-based Honey Badger Algorithm for Continuous Optimization, Cluster Computing 28(2), 2024.
  • Xu Y., Zhong R., Zhang C., Yu J., Crested Ibis Algorithm and Its Application in Human-Powered Aircraft Design, Knowledge-Based Systems 310, 2025.
  • Yang B., Zhang X., Yu T., Shu H., Fang Z., Grouped Grey Wolf Optimizer for Maximum Power Point Tracking of Doubly-Fed Induction Generator based Wind Turbine, Energy Conversion and Management 133, 427–443, 2017.
  • Yapici H., Cetinkaya N., A New Meta-Heuristic Optimizer: Pathfinder Algorithm, Applied Soft Computing Journal 78, 545–568, 2019.
  • Zhang S., Zhou Y., Li Z., Pan W., Grey Wolf Optimizer for Unmanned Combat Aerial Vehicle Path Planning, Advances in Engineering Software 99, 121–136, 2016.
  • Zhang S., Zhou Y., Grey Wolf Optimizer based on Powell Local Optimization Method for Clustering Analysis, Discrete Dynamics in Nature and Society 481360, 2015.
  • Zhong R., Yu J., Zhang C., Munetomo M., SRIME: A Strengthened RIME with Latin Hypercube Sampling and Embedded Distance-based Selection for Engineering Optimization Problems, Neural Computing and Applications 36(12), 2024.
  • Zhong R., Hussien A. G., Yu J., Munetomo M., LLMOA: A Novel Large Language Model Assisted Hyper-Heuristic Optimization Algorithm, Advanced Engineering Informatics 64, 2025.
  • Zhong R., Wang Z., Hussien A. G., Houssein E. H., Al-Shourbaji I., Elseify M. A., Yu J., Success History Adaptive Competitive Swarm Optimizer With Linear Population Reduction: Performance Benchmarking and Application in Eye Disease Detection, Computers in Biology and Medicine 186, 2025.
  • Zhong R., Zhang C., Yu J., Chaotic Vegetation Evolution: Leveraging Multiple Seeding Strategies and a Mutation Module for Global Optimization Problems, Evolutionary Intelligence 17(4), 2024.
  • Zhong R., Zhang C., Yu J., Cooperative Coati Optimization Algorithm with Transfer Functions for Feature Selection and Knapsack Problems, Knowledge and Information Systems, 66(11), 2024.
  • Zhou J., Zhu W., Zheng Y., Li C., Precise Equivalent Model of Small Hydro Generator Cluster and Its Parameter Identification using Improved Grey Wolf Optimiser, IET Generation, Transmission and Distribution 10(9), 2016.
Toplam 68 adet kaynakça vardır.

Ayrıntılar

Birincil Dil İngilizce
Konular Yazılım Mühendisliği (Diğer), Makine Mühendisliğinde Optimizasyon Teknikleri
Bölüm Araştırma Makaleleri
Yazarlar

Nermin Ozcan 0000-0001-5327-9090

Erken Görünüm Tarihi 15 Haziran 2025
Yayımlanma Tarihi 19 Haziran 2025
Gönderilme Tarihi 18 Mart 2025
Kabul Tarihi 6 Mayıs 2025
Yayımlandığı Sayı Yıl 2025 Cilt: 6 Sayı: 1

Kaynak Göster

APA Ozcan, N. (2025). Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems. Journal of Materials and Mechatronics: A, 6(1), 150-169. https://doi.org/10.55546/jmm.1660142
AMA Ozcan N. Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems. J. Mater. Mechat. A. Haziran 2025;6(1):150-169. doi:10.55546/jmm.1660142
Chicago Ozcan, Nermin. “Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems”. Journal of Materials and Mechatronics: A 6, sy. 1 (Haziran 2025): 150-69. https://doi.org/10.55546/jmm.1660142.
EndNote Ozcan N (01 Haziran 2025) Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems. Journal of Materials and Mechatronics: A 6 1 150–169.
IEEE N. Ozcan, “Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems”, J. Mater. Mechat. A, c. 6, sy. 1, ss. 150–169, 2025, doi: 10.55546/jmm.1660142.
ISNAD Ozcan, Nermin. “Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems”. Journal of Materials and Mechatronics: A 6/1 (Haziran 2025), 150-169. https://doi.org/10.55546/jmm.1660142.
JAMA Ozcan N. Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems. J. Mater. Mechat. A. 2025;6:150–169.
MLA Ozcan, Nermin. “Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems”. Journal of Materials and Mechatronics: A, c. 6, sy. 1, 2025, ss. 150-69, doi:10.55546/jmm.1660142.
Vancouver Ozcan N. Comprehensive Comparative Analysis of GWO and Its Variants for Solving Mechanical Optimization Problems. J. Mater. Mechat. A. 2025;6(1):150-69.
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