References
- Kennedy, J., R. C. Eberhart. Particle Swarm Optimization. – In: Proc. of IEEE International Conference on Neural Networks, 1995, pp. 1942-1948.
- Houssein, E. H., A. G. Gad, K. Hussain, P. N. Suganthan. Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application. – Swarm and Evolutionary Computation, Vol. 63, 2021, 100868. DOI: 10.1016/j.swevo.2021.100868.
- Freitas, D., L. G. Lopes, F. Morgado-Dias. Particle Swarm Optimisation: A Historical Review Up to the Current Developments. – Entropy, Vol. 22, 2020, No 3, 362. DOI: 10.3390/e22030362.
- Blackwell, T., J. Kennedy. Impact of Communication Topology in Particle Swarm Optimization. – IEEE Transactions on Evolutionary Computation, Vol. 23, 2019, No 4, pp. 689-702. DOI: 10.1109/tevc.2018.2880894.
- Kennedy, J., R. Mendes (n.d.). Population Structure and Particle Swarm Performance. – In: Proc. of Congress on Evolutionary Computation (CEC’02), 2002 (Cat. No 02TH8600). DOI: 10.1109/cec.2002.1004493.
- Engelbrecht, A. P. Particle Swarm Optimization: Global Best or Local Best? – In: Proc. of BRICS Congress on Computational Intelligence and 11th Brazilian Congress on Computational Intelligence, 2013. DOI: 10.1109/brics-cci-cbic.2013.31.
- Liu, H., B. Li, Y. Ji, T. Sun (n.d.). Particle Swarm Optimisation from lbest to gbest. – Applied Soft Computing Technologies: The Challenge of Complexity, pp. 537-545. DOI: 10.1007/3-540-31662-0_41.
- Vazquez, J. C., F. Valdez, P. Melin. Comparative Study of Social Network Structures in PSO. – Recent Advances on Hybrid Approaches for Designing Intelligent Systems, 2014, pp. 239-254. DOI: 10.1007/978-3-319-05170-3_17.
- Ahmed, G. G. Particle Swarm Optimization Algorithm and Its Applications: A Systematic Review. – Archives of Computational Methods in Engineering, Vol. 29, 2022, pp. 2531-2561. DOI: 10.1007/s11831-021-09694-4.
- Shami, T. M., A. A. El-Saleh, M. Alswaitti, Q. Al-Tashi, M. A. Summakieh, S. Mirjalili. Particle Swarm Optimization: A Comprehensive Survey. – IEEE Access, Vol. 10, 2022, pp. 10031-10061. DOI: 10.1109/ACCESS.2022.3142859
- Houssein, E. H., A. G. Gad, K. Hussain, P. N. Suganthan. Major Advances in Particle Swarm Optimization: Theory, Analysis, and Application. – Swarm and Evolutionary Computation, Vol. 63, 2021, 100868. DOI: 10.1016/j.swevo.2021.100868.
- Yudong, Z., W. Shuihua, J. Genlin. A Comprehensive Survey on Particle Swarm Optimization. Algorithm and Its Applications. – Mathematical Problems in Engineering, Vol. 38, 2015, 931256. DOI: org/10.1155/2015/931256.
- Pluhacek, M., A. Kazikova, T. Kadavy, A. Viktorin, R. Senkerik. Relation of Neighborhood Size and Diversity Loss Rate in Particle Swarm Optimization with Ring Topology. Mendel. – Soft Computing Journal, Vol. 27, 2021, No 2, pp. 74-79. DOI: 10.13164/mendel.2021.k.0d9.
- Ni, J. C., L. Li, F. Qiao. A Topology Based on a Local World Evolving Model for PSO. – Advanced Materials Research, Vol. 219-220, 2011, pp. 1297-1300. DOI: 10.4028/www.scientific.net/amr.219-220.1297.
- Ghosh, S., D. Kundu, K. Suresh, S. Das, A. Abraham, B. K. Panigrahi, V. Snasel. On Some Properties of the lbest Topology in Particle Swarm Optimization. – In: Proc. of 9th International Conference on Hybrid Intelligent Systems, 2009. DOI: 10.1109/his.2009.288.
- Fernandes, C. M., A. C. Rosa, J. L. J. Laredo, C. Cotta, J. J. Merelo. A Study on Time-Varying Partially Connected Topologies for the Particle Swarm. – In: Proc. of IEEE Congress on Evolutionary Computation, 2013. DOI: 10.1109/cec.2013.6557863.
- Tsujimoto, T., T. Shindo, T. Kimura, K. Jin’no. A Relationship between Network Topology and Search Performance of PSO. – In: Proc. of IEEE Congress on Evolutionary Computation. 2,012. DOI: 10.1109/cec.2012.6256536.
- Suganthan, P. N. Particle Swarm Optimiser with Neighbourhood Operator. – In: Proc. of Congress on Evolutionary Computation-CEC99 (Cat. No 99TH8406), Washington, DC, USA, Vol. 3, 1999, pp. 1958-1962. DOI: 10.1109/CEC.1999.785514.
- Kennedy, J. Stereotyping: Improving Particle Swarm Performance with Cluster Analysis. – In: Proc. of Congress on Evolutionary Computation. CEC00 (Cat. No 00TH8512), La Jolla, CA, USA, Vol. 2, 2000, pp. 1507-1512. DOI: 10.1109/CEC.2000.870832.
- Parsopoulus, K. E., N. M. Vrahatis. UPSO: A Unified Particle Swarm Optimization Scheme. – Lecture Series on Computational Siences, 2004, No 1, pp. 868-873.
- Marinakis, Y., A. Migdalas, A. Sifaleras. A Hybrid Particle Swarm Optimization – Variable Neighborhood Search Algorithm for Constrained Shortest Path Problems. – European Journal of Operational Research, Vol. 261, 2017, No 3, pp. 819-834. DOI: 10.1016/j.ejor.2017.03.031.
- Wei, S., L. Anping, Y. Hongshan, L. Qiaokang, W. Guohua. All-Dimension Neighborhood Based Particle Swarm Optimization with Randomly Selected Neighbors. – Information Sciences, 2017, pp. 1-22. DOI: 10.1016/j.ins.2017.04.007.
- H. Ishibuchi, Q. Zhang, R. Cheng, K. Li, H. Li, H. Wang, A. Zhou, Eds. Evolutionary Multi-Criterion Optimization. – In: Lecture Notes in Computer Science. 2021. DOI:10.1007/978-3-030-72062-9.
- Lynn, N., M. Z. Ali, P. N. Suganthan. Population Topologies for Particle Swarm Optimization and Differential Evolution. – Swarm and Evolutionary Computation, Vol. 39, 2018, pp. 24-35. DOI: 10.1016/j.swevo.2017.11.002.
- Li, X. Niching without Niching Parameters: Particle Swarm Optimization Using a Ring Topology. – IEEE Transactions on Evolutionary Computation, Vol. 14, 2010, No 1, pp. 150-169, 5352335. DOI: 10.1109/TEVC.2009.2026270.
- Romasevych, Y., V. Loveikin, Y. Loveikin. Development of New Rotating Ring Topology of PSO-Algorithm. – In: Proc. of 2nd IEEE KhPI Week on Advanced Technology (KhPIWeek’21), Kharkiv, Ukraine, 2021, pp. 79-82. DOI: 10.1109/KhPIWeek53812.2021.9569973.
- Storn, R., K. Price. Differential Evolution – A Simple and Efficient Heuristic for Global Optimization Over Continuous Spaces. – Journal of Global Optimization, Vol. 11, 1997, No 4, pp. 341-359.
- Optimization & Eye Pleasure: 78 Benchmark Test Functions for Single Objective Optimization. https://towardsdatascience.com/optimization-eye-pleasure-78-benchmark-test-functions-for-single-objective-optimization-92e7ed1d1f12
- Virtual Library of Simulation Experiments: Test Functions and Datasets. Optimization Test Problems. https://www.sfu.ca/~ssurjano/optimization.html
- HappyCat – A Simple Function Class Where Well-Known Direct Search Algorithms Do Fail. https://homepages.fhv.at/hgb/New-Papers/PPSN12_BF12.pdf
- Momin, J., Y. Xin-She. A Literature Survey of Benchmark Functions for Global Optimization Problems. – Int. Journal of Mathematical Modelling and Numerical Optimisation, Vol. 4, 2013, No 2, pp. 150-194. DOI: 10.1504/IJMMNO.2013.055204.
- Montaz, A. M., C. Khompatraporn, Z. B. Zabinsky. A Numerical Evaluation of Several Stochastic Algorithms on Selected Continuous Global Optimization Test Problems. – Journal of Global Optimization, Vol. 31, 2005, pp. 635-672. DOI: 10.1007/s10898-004-9972-2.
- Romasevych, Y., V. Loveikin, V. Makarets. Optimal Constrained Tuning of PI-Controllers via a New PSO-Based Technique. – International Journal of Swarm Intelligence Research, Vol. 11, 2020, No 4, pp. 87-105. DOI: 10.4018/IJSIR.2020100104.
- Shi, Y., R. Eberhart. A Modified Particle Swarm Optimizer. – In: Proc. of IEEE International Conference on Evolutionary Computation Proceedings. IEEE World Congress on Computational Intelligence, 1998, pp. 69-73. DOI: 10.1109/ICEC.1998.699146.
- Romasevych, Y., V. Loveikin, Y. Loveikin. Development of a PSO Modification with Varying Cognitive Term. – In: Proc. of 3rd IEEE KhPI Week on Advanced Technology (KhPIWeek), IEEE, 2022, pp. 55-59. DOI: 10.1109/KhPIWeek57572.2022.9916413.
- Article Additional Data. https://drive.google.com/file/d/1Oj5-GzgczntCWHDRYazkIhjvTkpHTzW8/view?usp=sharing
- Romasevych, Y., V. Loveikin, M. Ohiienko, L. Shymko, K. Łukawiecki. Innovation Management in Agriculture. Agrotronics and Design of Optimal Controllers Based on New Modifications of Particle Swarm Optimization, 2021. https://www.wszia.opole.pl/wp-content/uploads/2020/09/Mon_Romasevich.pdf
- Cazzolato, B. S., Z. Prime. On the Dynamics of the Furuta Pendulum. – Journal of Control Science and Engineering, 2011, Article ID 528341. 8 p. DOI: 10.1155/2011/528341.
- Antonio-Cruz, M., V. M. Hernandez-Guzman, C. A. Merlo-Zapata, C. Marquez-Sanchez. Nonlinear Control with Friction Compensation to Swing-Up a Furuta Pendulum. – ISA Transactions, Vol. 139, 2023, pp. 713-723. DOI: 10.1016/j.isatra.2023.05.007.
- Dallali, H., P. Kormushev, Z. Li, D. Caldwell. On Global Optimization of Walking Gaits for the Compliant Humanoid Robot, COMAN Using Reinforcement Learning. – Cybernetics and Information Technologies, Vol. 12, 2012, No 3, pp. 39-52.
- Huang, Z., F. Huang, X. Wang, F. Chu. Active Vibration Control of Composite Cantilever Beams. – Materials, Vol. 16, 2023, 95. DOI: 10.3390/ma16010095.
- Huang, Z., Y. Mao, A. Dai, M. Han, X. Wang, F. Chu. Active Vibration Control of Piezoelectric Sandwich Plates. – Materials, Vol. 15, 2022, 3907. DOI: 10.3390/ma15113907.
- Xin, Z., D. Gao, S. Lu, X. Fu, Y. Zhu, J. Xu. Research of Active Vibration Control for Cantilever Beam Based on Macro Fiber Composite Actuators. – In: Proc. of International Conference on Cyber-Physical Social Intelligence (ICCSI’22), Nanjing, China, 2022, pp. 573-577. DOI: 10.1109/ICCSI55536.2022.9970636.