A Novel Multi-Epoch Particle Swarm Optimization Technique

1. Bozorg-Haddad, O., M. Solgi, H. A. Loáiciga. Meta-Heuristic and Evolutionary Algorithms for Engineering Optimization. Hoboken, USA, John Wiley & Sons Inc, 2017.10.1002/9781119387053Search in Google Scholar

2. Kennedy, J., R. C. Eberhart. Particle Swarm Optimization. – In: Proc. of IEEE International Conference on Neural Networks, 1995, pp. 1942-1948.Search in Google Scholar

3. Kiranyaz, S., T. Ince, A. Yildirim, M. Gabbouj. Evolutionary Artificial Neural Networks by Multi-Dimensional Particle Swarm Optimization. – Neural Networks, Vol. 22, 2009, Issue 10, pp. 1448-1462.10.1016/j.neunet.2009.05.01319556105Search in Google Scholar

4. Heo, J. S., K. Y. Lee, R. Garduno-Ramirez. Multiobjective Control of Power Plants Using Particle Swarm Optimization Techniques. – IEEE Transactions on Energy Conversion, Vol. 21, 2006, Issue 10, pp. 552-561.10.1109/TEC.2005.858078Search in Google Scholar

5. Zamani, M., M. Karimi-Ghartemani, N. Sadati, M. Parniani. Design of a Fractional Order PID Controller for an AVR Using Particle Swarm Optimization. – Control Engineering Practice, Vol. 17, 2009, Issue 12, pp. 1380-1387.10.1016/j.conengprac.2009.07.005Search in Google Scholar

6. Chander, A., A. Chatterjee, P. Siarry. A New Social and Momentum Component Adaptive PSO Algorithm for Image Segmentation. – Expert Systems with Applications, Vol. 38, 2011, Issue 5, pp. 4998-5004.10.1016/j.eswa.2010.09.151Search in Google Scholar

7. Bordbar, S., P. Shamsinejad. A New Opinion Mining Method Based on Fuzzy Classifier and Particle Swarm Optimization (PSO) Algorithm. – Cybernetics and Information Technologies, Vol. 18, 2018, No 2, pp. 36-50.10.2478/cait-2018-0026Search in Google Scholar

8. He, Q., Y. Lv. Particle Swarm Optimization Based on Smoothing Approach for Solving a Class of Bi-Level Multiobjective Programming Problem. – Cybernetics and Information Technologies, Vol. 17, 2017, No 3, pp. 59-74.10.1515/cait-2017-0030Search in Google Scholar

9. Bao, G. Q., D. Zhang, J. H. Shi, J. Z. Jiang. Optimal Design for Cogging Torque Reduction of Transverse Flux Permanent Motor Using Particle Swarm Optimization Algorithm. – Power Electronics and Motion Control Conference, Vol. 4, 2004.Search in Google Scholar

10. Shurub, Y. V., A. O. Dudnyk, D. S. Lavinskiy. Optimization of Regulators of Frequency Controlled Induction Electric Drives under the Stochastic Loadings. – Journal Tekhnichna Elektrodynamika, Vol. 4, 2016, pp. 53-55.10.15407/techned2016.04.053Search in Google Scholar

11. Taher, N. A New Fuzzy Adaptive Hybrid Particle Swarm Optimization Algorithm for Non-Linear, Non-Smooth and Non-Convex Economic Dispatch Problem. – Applied Energy, Vol. 87, 2010, Issue 1, pp. 327-339.10.1016/j.apenergy.2009.05.016Search in Google Scholar

12. Rao, R. V., V. J. Savsani, D. P. Vakharia. Teaching-Learning-Based Optimization: An Optimization Method for Continuous Non-Linear Large Scale Problems. – Information Sciences, Vol. 183, 2012, Issue 1, pp. 1-15.10.1016/j.ins.2011.08.006Search in Google Scholar

13. Liu, D., K. C. Tan, C. K. Goh, W. K. Ho. A Multiobjective Memetic Algorithm Based on Particle Swarm Optimization. – IEEE Transactions on Systems Man and Cybernetics, Part B (Cybernetics), Vol. 37, 2007, Issue 1, pp. 42-50.10.1109/TSMCB.2006.883270Search in Google Scholar

14. Loveikin, V. S., Y. O. Romasevych. Dynamic Optimization of a Mine Winder Acceleration Mod. – Naukovyi Visnyk Natsionalnoho Hirnychoho Universytetu, Vol. 4, 2017, pp. 55-61.Search in Google Scholar

15. Clerc, M. Back to random topology [Electronic resource]. http://clerc.maurice.free.fr/pso/random_topology.pdfSearch in Google Scholar

16. Richards, M., D. Ventura. Dynamic Sociometry in Particle Swarm Optimization. – In: Proc. of Joint Conference of Information Sciences, 2003, pp. 1557-1560.Search in Google Scholar

17. Clerc, M. Variable PSO [Electronic resource]. http://clerc.maurice.free.fr/pso/2011-01-20_Variable_PSO.zipSearch in Google Scholar

18. Suresh, K., S. Ghosh, D. Kundu, A. Sen. Inertia-Adaptive Particle Swarm Optimizer for Improved Global Search. – Intelligent Systems Design and Applications, 2008.10.1109/ISDA.2008.199Search in Google Scholar

19. Yong, D., W. Wu Chuansheng, G. Haimin. Particle Swarm Optimization Algorithm with Adaptive Chaos Perturbation. – Cybernetics and Information Technologies, Special Issue on Logistics, Informatics and Service Science, Vol. 15, 2015, No 6, pp. 70-80.10.1515/cait-2015-0068Search in Google Scholar

20. Jordan, J., S. Helwing, R. Wanka. Social Interaction in Particle Swarm Optimization, the Ranked FIPS, and Adaptive Multi-Swarms. – In: Proc. of 10th Annual Conference on Genetic and Evolutionary Computation, 2008, pp. 49-56.10.1145/1389095.1389103Search in Google Scholar

21. Parsopoulos, K. E. Parallel Cooperative Micro-Particle Swarm Optimization: A Master-Slave Model. – Applied Soft Computing, Vol. 12, 2012, Issue 11, pp. 3552-3579.10.1016/j.asoc.2012.07.013Search in Google Scholar

22. Garg, H. A Hybrid PSO-GA Algorithm for Constrained Optimization Problems. – Applied Mathematics and Computation, Vol. 274, 2016, pp. 292-305.10.1016/j.amc.2015.11.001Search in Google Scholar