Research Article
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Year 2025, Volume: 12 Issue: 2, 392 - 416, 30.06.2025
https://doi.org/10.54287/gujsa.1667182

Abstract

References

  • Abdel-Basset, M., Mohamed, R., & Abouhawwash, M. (2025). Fungal growth optimizer: A novel nature-inspired metaheuristic algorithm for stochastic optimization. Computer Methods in Applied Mechanics and Engineering, 437, 117825. https://doi.org/10.1016/j.cma.2025.117825
  • Abdollahzadeh, B., Soleimanian Gharehchopogh, F., & Mirjalili, S. (2021). Artificial gorilla troops optimizer: A new nature-inspired metaheuristic algorithm for global optimization problems. International Journal of Intelligent Systems, 36(10), 5887-5958. https://doi.org/10.1002/int.22535
  • Aribowo, W., Abualigah, L., Oliva, D., Mzili, T., Sabo, A., & A. Shehadeh, H. (2024). Frilled Lizard Optimization to optimize parameters Proportional Integral Derivative of DC Motor. Vokasi Unesa Bulletin of Engineering, Technology and Applied Science, 1(1), 14-21. https://doi.org/10.26740/vubeta.v1i1.33973
  • Aribowo, W., Rahmadian, R., & Widyartono, M. (2023). Adaptive tuning of PID using chef‑based optimization algorithm for improving automatic voltage regulator. Indonesian Journal of Electrical Engineering and Computer Science, 32(3), 1215-1223. https://doi.org/10.11591/ijeecs.v32.i3.pp1215-1223
  • Bai, B., Zhang, J., Wu, X., wei Zhu, G., & Li, X. (2021). Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems. Expert Systems with Applications, 177, 114952. https://doi.org/10.1016/j.eswa.2021.114952
  • Bakır, H., Duman, S., Guvenc, U., & Kahraman, H. T. (2023). Improved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problem. Electrical Engineering, 105(5), 3121-3160. https://doi.org/10.1007/s00202-023-01803-9
  • Balasubramaniam, S., Kadry, S., Dhanaraj, R. K., Satheesh Kumar, K., & Manthiramoorthy, C. (2024). Res-Unet based blood vessel segmentation and cardio vascular disease prediction using chronological chef-based optimization algorithm based deep residual network from retinal fundus images. Multimedia Tools and Applications, 83(40), 87929-87958. https://doi.org/10.1007/s11042-024-18810-y
  • Beşkirli, M. (2021). Solving continuous optimization problems using the tree seed algorithm developed with the roulette wheel strategy. Expert Systems with Applications, 170, 114579. https://doi.org/10.1016/j.eswa.2021.114579
  • Dehghani, M., Montazeri, Z., Trojovská, E., & Trojovský, P. (2023). Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems. Knowledge-Based Systems, 259, 110011. https://doi.org/10.1016/j.knosys.2022.110011
  • Demirbas, M., Dosoglu, M. K., & Duman, S. (2025). Enhanced Coati Optimization Algorithm for Static and Dynamic Transmission Network Expansion Planning Problems. IEEE Access, 13, 35068-35100. https://doi.org/10.1109/ACCESS.2025.3544523
  • Dhopavkar, T. A., Nayak, S. K., & Roy, S. (2022). IETD: a novel image encryption technique using Tinkerbell map and Duffing map for IoT applications. Multimedia Tools and Applications, 81(30), 43189-43228. https://doi.org/10.1007/s11042-022-13162-x
  • Fu, Y., Liu, D., Chen, J., & He, L. (2024). Secretary bird optimization algorithm: a new metaheuristic for solving global optimization problems. Artificial Intelligence Review, 57(5), 123. https://doi.org/10.1007/s10462-024-10729-y
  • Ghasemi, M., Zare, M., Zahedi, A., Akbari, M.-A., Mirjalili, S., & Abualigah, L. (2024). Geyser Inspired Algorithm: A New Geological-inspired Meta-heuristic for Real-parameter and Constrained Engineering Optimization. Journal of Bionic Engineering, 21(1), 374-408. https://doi.org/10.1007/s42235-023-00437-8
  • Hashim, F. A., Houssein, E. H., Hussain, K., Mabrouk, M. S., & Al-Atabany, W. (2022). Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems. Mathematics and Computers in Simulation, 192, 84-110. https://doi.org/10.1016/j.matcom.2021.08.013
  • Huang, Q., Ding, H., & Effatparvar, M. (2024). Breast cancer diagnosis based on hybrid SqueezeNet and improved chef-based optimizer. Expert Systems with Applications, 237, 121470. https://doi.org/10.1016/j.eswa.2023.121470
  • Joni, K. (2024). Parameter Estimation Of Photovoltaic based on Chaotic Elite Mountain Gazelle Optimizer. Vokasi Unesa Bulletin of Engineering, Technology and Applied Science, 1(1), 30-37. https://doi.org/10.26740/vubeta.v1i1.34073
  • Kahraman, H. T., Aras, S., & Gedikli, E. (2020). Fitness-distance balance (FDB): A new selection method for meta-heuristic search algorithms. Knowledge-Based Systems, 190, 105169. https://doi.org/10.1016/j.knosys.2019.105169
  • Kaveh, A., & Mahjoubi, S. (2019). Hypotrochoid spiral optimization approach for sizing and layout optimization of truss structures with multiple frequency constraints. Engineering with Computers, 35(4), 1443-1462. https://doi.org/10.1007/s00366-018-0675-6
  • Kiran, M. S. (2015). TSA: Tree-seed algorithm for continuous optimization. Expert Systems with Applications, 42(19), 6686-6698. https://doi.org/10.1016/j.eswa.2015.04.055
  • Kiran, M. S., & Beskirli, M. (2024). A New Approach Based on Collective Intelligence to Solve Traveling Salesman Problems. Biomimetics, 9(2), 118. https://doi.org/10.3390/biomimetics9020118
  • Kutlu Onay, F. (2023). A novel improved chef-based optimization algorithm with Gaussian random walk-based diffusion process for global optimization and engineering problems. Mathematics and Computers in Simulation, 212, 195-223. https://doi.org/10.1016/j.matcom.2023.04.027
  • Liu, Q., Sun, K., Tang, X., & Huo, J. (2024). Camera calibration based on lightweight fan-shaped target detection and fitness-distance-balance chaotic marine predators algorithm. Optics & Laser Technology, 176, 110883. https://doi.org/10.1016/j.optlastec.2024.110883
  • Mirjalili, S., & Gandomi, A. H. (2017). Chaotic gravitational constants for the gravitational search algorithm. Applied Soft Computing, 53, 407-419. https://doi.org/10.1016/j.asoc.2017.01.008
  • Mirjalili, S., & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. https://doi.org/10.1016/j.advengsoft.2016.01.008
  • Öztürk, H. T., & Kahraman, H. T. (2025). Metaheuristic search algorithms in frequency constrained truss problems: Four improved evolutionary algorithms, optimal solutions and stability analysis. Applied Soft Computing, 171, 112854. https://doi.org/10.1016/j.asoc.2025.112854
  • Prapanca, A., Nasreddine, B., & Imed, M. (2025). Modified FATA Morgana Algorithm Based on Levy Flight. Vokasi Unesa Bulletin of Engineering, Technology and Applied Science, 2(1), 1-11. https://doi.org/10.26740/vubeta.v2i1.37066
  • Rajesh Kumar, T., Enireddy, V., Kalai Selvi, K., Shahid, M., Vijendra Babu, D., & Sudha, I. (2024). Fractional chef based optimization algorithm trained deep learning for cardiovascular risk prediction using retinal fundus images. Biomedical Signal Processing and Control, 94, 106269. https://doi.org/10.1016/j.bspc.2024.106269 Trojovská, E., & Dehghani, M. (2022). A new human-based metahurestic optimization method based on mimicking cooking training. Scientific Reports, 12(1), 14861. https://doi.org/10.1038/s41598-022-19313-2
  • Trojovská, E., Dehghani, M., & Trojovský, P. (2022). Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm. IEEE Access, 10, 49445-49473. https://doi.org/10.1109/ACCESS.2022.3172789
  • Trojovský, P. (2023). A new human-based metaheuristic algorithm for solving optimization problems based on preschool education. Scientific Reports, 13(1), 21472. https://doi.org/10.1038/s41598-023-48462-1
  • Trojovský, P., & Dehghani, M. (2022). Pelican Optimization Algorithm: A Novel Nature-Inspired Algorithm for Engineering Applications. Sensors, 22(3), 855. https://doi.org/10.3390/s22030855
  • Turkoglu, B., Uymaz, S. A., & Kaya, E. (2025). Chaotic Artificial Algae Algorithm for Solving Global Optimization With Real-World Space Trajectory Design Problems. Arabian Journal for Science and Engineering, 50(2), 1279-1306. https://doi.org/10.1007/s13369-024-09222-z
  • Wang, G.-G., Guo, L., Gandomi, A. H., Hao, G.-S., & Wang, H. (2014). Chaotic Krill Herd algorithm. Information Sciences, 274, 17-34. https://doi.org/10.1016/j.ins.2014.02.123
  • Zhang, W., Zhao, J., Liu, H., & Tu, L. (2024). Cleaner fish optimization algorithm: a new bio-inspired meta-heuristic optimization algorithm. The Journal of Supercomputing, 80(12), 17338-17376. https://doi.org/10.1007/s11227-024-06105-w
  • Zhao, W., Wang, L., & Zhang, Z. (2019). Atom search optimization and its application to solve a hydrogeologic parameter estimation problem. Knowledge-Based Systems, 163, 283-304. https://doi.org/10.1016/j.knosys.2018.08.030

Improved Chef-Based Optimization Algorithm with Chaos-Based Fitness Distance Balance for Frequency-Constrained Truss Structures

Year 2025, Volume: 12 Issue: 2, 392 - 416, 30.06.2025
https://doi.org/10.54287/gujsa.1667182

Abstract

Chef-based optimization algorithm (CBOA), one of the recently proposed metaheuristic algorithms, is a population-based optimization algorithm inspired by the process of students becoming skilled chefs after receiving training from chef instructors in a culinary academy. In order to improve the performance of CBOA, seven different CBOA variants are proposed in this study, which are improved with three different chaotic maps, fitness distance balance strategy and their combinations. The effectiveness of the proposed CBOA variants is first evaluated by testing them on 16 different benchmark functions. Then, the proposed CBOA variants are applied to frequency constrained 37-bar and 52-bar truss problems to evaluate their performance on engineering problems. Thus, the success of the proposed CBOA variants on different problems was extensively investigated in three different experimental studies. Among these variants, while FC2-CBOA and FC3-CBOA variants performed well on benchmark functions, FC3-CBOA and C3-CBOA variants performed well on 37-bar and 52-bar truss problems, respectively. The results obtained from these three different experimental studies have shown that each proposed CBOA variant is able to produce effective results depending on the problem type.

References

  • Abdel-Basset, M., Mohamed, R., & Abouhawwash, M. (2025). Fungal growth optimizer: A novel nature-inspired metaheuristic algorithm for stochastic optimization. Computer Methods in Applied Mechanics and Engineering, 437, 117825. https://doi.org/10.1016/j.cma.2025.117825
  • Abdollahzadeh, B., Soleimanian Gharehchopogh, F., & Mirjalili, S. (2021). Artificial gorilla troops optimizer: A new nature-inspired metaheuristic algorithm for global optimization problems. International Journal of Intelligent Systems, 36(10), 5887-5958. https://doi.org/10.1002/int.22535
  • Aribowo, W., Abualigah, L., Oliva, D., Mzili, T., Sabo, A., & A. Shehadeh, H. (2024). Frilled Lizard Optimization to optimize parameters Proportional Integral Derivative of DC Motor. Vokasi Unesa Bulletin of Engineering, Technology and Applied Science, 1(1), 14-21. https://doi.org/10.26740/vubeta.v1i1.33973
  • Aribowo, W., Rahmadian, R., & Widyartono, M. (2023). Adaptive tuning of PID using chef‑based optimization algorithm for improving automatic voltage regulator. Indonesian Journal of Electrical Engineering and Computer Science, 32(3), 1215-1223. https://doi.org/10.11591/ijeecs.v32.i3.pp1215-1223
  • Bai, B., Zhang, J., Wu, X., wei Zhu, G., & Li, X. (2021). Reliability prediction-based improved dynamic weight particle swarm optimization and back propagation neural network in engineering systems. Expert Systems with Applications, 177, 114952. https://doi.org/10.1016/j.eswa.2021.114952
  • Bakır, H., Duman, S., Guvenc, U., & Kahraman, H. T. (2023). Improved adaptive gaining-sharing knowledge algorithm with FDB-based guiding mechanism for optimization of optimal reactive power flow problem. Electrical Engineering, 105(5), 3121-3160. https://doi.org/10.1007/s00202-023-01803-9
  • Balasubramaniam, S., Kadry, S., Dhanaraj, R. K., Satheesh Kumar, K., & Manthiramoorthy, C. (2024). Res-Unet based blood vessel segmentation and cardio vascular disease prediction using chronological chef-based optimization algorithm based deep residual network from retinal fundus images. Multimedia Tools and Applications, 83(40), 87929-87958. https://doi.org/10.1007/s11042-024-18810-y
  • Beşkirli, M. (2021). Solving continuous optimization problems using the tree seed algorithm developed with the roulette wheel strategy. Expert Systems with Applications, 170, 114579. https://doi.org/10.1016/j.eswa.2021.114579
  • Dehghani, M., Montazeri, Z., Trojovská, E., & Trojovský, P. (2023). Coati Optimization Algorithm: A new bio-inspired metaheuristic algorithm for solving optimization problems. Knowledge-Based Systems, 259, 110011. https://doi.org/10.1016/j.knosys.2022.110011
  • Demirbas, M., Dosoglu, M. K., & Duman, S. (2025). Enhanced Coati Optimization Algorithm for Static and Dynamic Transmission Network Expansion Planning Problems. IEEE Access, 13, 35068-35100. https://doi.org/10.1109/ACCESS.2025.3544523
  • Dhopavkar, T. A., Nayak, S. K., & Roy, S. (2022). IETD: a novel image encryption technique using Tinkerbell map and Duffing map for IoT applications. Multimedia Tools and Applications, 81(30), 43189-43228. https://doi.org/10.1007/s11042-022-13162-x
  • Fu, Y., Liu, D., Chen, J., & He, L. (2024). Secretary bird optimization algorithm: a new metaheuristic for solving global optimization problems. Artificial Intelligence Review, 57(5), 123. https://doi.org/10.1007/s10462-024-10729-y
  • Ghasemi, M., Zare, M., Zahedi, A., Akbari, M.-A., Mirjalili, S., & Abualigah, L. (2024). Geyser Inspired Algorithm: A New Geological-inspired Meta-heuristic for Real-parameter and Constrained Engineering Optimization. Journal of Bionic Engineering, 21(1), 374-408. https://doi.org/10.1007/s42235-023-00437-8
  • Hashim, F. A., Houssein, E. H., Hussain, K., Mabrouk, M. S., & Al-Atabany, W. (2022). Honey Badger Algorithm: New metaheuristic algorithm for solving optimization problems. Mathematics and Computers in Simulation, 192, 84-110. https://doi.org/10.1016/j.matcom.2021.08.013
  • Huang, Q., Ding, H., & Effatparvar, M. (2024). Breast cancer diagnosis based on hybrid SqueezeNet and improved chef-based optimizer. Expert Systems with Applications, 237, 121470. https://doi.org/10.1016/j.eswa.2023.121470
  • Joni, K. (2024). Parameter Estimation Of Photovoltaic based on Chaotic Elite Mountain Gazelle Optimizer. Vokasi Unesa Bulletin of Engineering, Technology and Applied Science, 1(1), 30-37. https://doi.org/10.26740/vubeta.v1i1.34073
  • Kahraman, H. T., Aras, S., & Gedikli, E. (2020). Fitness-distance balance (FDB): A new selection method for meta-heuristic search algorithms. Knowledge-Based Systems, 190, 105169. https://doi.org/10.1016/j.knosys.2019.105169
  • Kaveh, A., & Mahjoubi, S. (2019). Hypotrochoid spiral optimization approach for sizing and layout optimization of truss structures with multiple frequency constraints. Engineering with Computers, 35(4), 1443-1462. https://doi.org/10.1007/s00366-018-0675-6
  • Kiran, M. S. (2015). TSA: Tree-seed algorithm for continuous optimization. Expert Systems with Applications, 42(19), 6686-6698. https://doi.org/10.1016/j.eswa.2015.04.055
  • Kiran, M. S., & Beskirli, M. (2024). A New Approach Based on Collective Intelligence to Solve Traveling Salesman Problems. Biomimetics, 9(2), 118. https://doi.org/10.3390/biomimetics9020118
  • Kutlu Onay, F. (2023). A novel improved chef-based optimization algorithm with Gaussian random walk-based diffusion process for global optimization and engineering problems. Mathematics and Computers in Simulation, 212, 195-223. https://doi.org/10.1016/j.matcom.2023.04.027
  • Liu, Q., Sun, K., Tang, X., & Huo, J. (2024). Camera calibration based on lightweight fan-shaped target detection and fitness-distance-balance chaotic marine predators algorithm. Optics & Laser Technology, 176, 110883. https://doi.org/10.1016/j.optlastec.2024.110883
  • Mirjalili, S., & Gandomi, A. H. (2017). Chaotic gravitational constants for the gravitational search algorithm. Applied Soft Computing, 53, 407-419. https://doi.org/10.1016/j.asoc.2017.01.008
  • Mirjalili, S., & Lewis, A. (2016). The Whale Optimization Algorithm. Advances in Engineering Software, 95, 51-67. https://doi.org/10.1016/j.advengsoft.2016.01.008
  • Öztürk, H. T., & Kahraman, H. T. (2025). Metaheuristic search algorithms in frequency constrained truss problems: Four improved evolutionary algorithms, optimal solutions and stability analysis. Applied Soft Computing, 171, 112854. https://doi.org/10.1016/j.asoc.2025.112854
  • Prapanca, A., Nasreddine, B., & Imed, M. (2025). Modified FATA Morgana Algorithm Based on Levy Flight. Vokasi Unesa Bulletin of Engineering, Technology and Applied Science, 2(1), 1-11. https://doi.org/10.26740/vubeta.v2i1.37066
  • Rajesh Kumar, T., Enireddy, V., Kalai Selvi, K., Shahid, M., Vijendra Babu, D., & Sudha, I. (2024). Fractional chef based optimization algorithm trained deep learning for cardiovascular risk prediction using retinal fundus images. Biomedical Signal Processing and Control, 94, 106269. https://doi.org/10.1016/j.bspc.2024.106269 Trojovská, E., & Dehghani, M. (2022). A new human-based metahurestic optimization method based on mimicking cooking training. Scientific Reports, 12(1), 14861. https://doi.org/10.1038/s41598-022-19313-2
  • Trojovská, E., Dehghani, M., & Trojovský, P. (2022). Zebra Optimization Algorithm: A New Bio-Inspired Optimization Algorithm for Solving Optimization Algorithm. IEEE Access, 10, 49445-49473. https://doi.org/10.1109/ACCESS.2022.3172789
  • Trojovský, P. (2023). A new human-based metaheuristic algorithm for solving optimization problems based on preschool education. Scientific Reports, 13(1), 21472. https://doi.org/10.1038/s41598-023-48462-1
  • Trojovský, P., & Dehghani, M. (2022). Pelican Optimization Algorithm: A Novel Nature-Inspired Algorithm for Engineering Applications. Sensors, 22(3), 855. https://doi.org/10.3390/s22030855
  • Turkoglu, B., Uymaz, S. A., & Kaya, E. (2025). Chaotic Artificial Algae Algorithm for Solving Global Optimization With Real-World Space Trajectory Design Problems. Arabian Journal for Science and Engineering, 50(2), 1279-1306. https://doi.org/10.1007/s13369-024-09222-z
  • Wang, G.-G., Guo, L., Gandomi, A. H., Hao, G.-S., & Wang, H. (2014). Chaotic Krill Herd algorithm. Information Sciences, 274, 17-34. https://doi.org/10.1016/j.ins.2014.02.123
  • Zhang, W., Zhao, J., Liu, H., & Tu, L. (2024). Cleaner fish optimization algorithm: a new bio-inspired meta-heuristic optimization algorithm. The Journal of Supercomputing, 80(12), 17338-17376. https://doi.org/10.1007/s11227-024-06105-w
  • Zhao, W., Wang, L., & Zhang, Z. (2019). Atom search optimization and its application to solve a hydrogeologic parameter estimation problem. Knowledge-Based Systems, 163, 283-304. https://doi.org/10.1016/j.knosys.2018.08.030
There are 34 citations in total.

Details

Primary Language English
Subjects Artificial Intelligence (Other)
Journal Section Computer Engineering
Authors

Ayşe Beşkirli 0000-0002-8694-8438

Early Pub Date June 10, 2025
Publication Date June 30, 2025
Submission Date March 27, 2025
Acceptance Date May 8, 2025
Published in Issue Year 2025 Volume: 12 Issue: 2

Cite

APA Beşkirli, A. (2025). Improved Chef-Based Optimization Algorithm with Chaos-Based Fitness Distance Balance for Frequency-Constrained Truss Structures. Gazi University Journal of Science Part A: Engineering and Innovation, 12(2), 392-416. https://doi.org/10.54287/gujsa.1667182