Novel Gaussian quantum-behaved particle swarm optimiser applied to electromagnetic design

IET Science, Measurement and Technology

Volumn 1, Issue 5, 2007, Pages 290-294

  Coelho, L S ^a  

^a PONTIFICAL CATHOLIC UNIVERSITY OF PARANÁ   (Brazil)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTER SIMULATION; EVOLUTIONARY ALGORITHMS; GAUSSIAN BEAMS; GAUSSIAN DISTRIBUTION; PSYCHOLOGY COMPUTING; QUANTUM THEORY;

ELECTROMAGNETIC DESIGN; METAPHOR; PARTICLE SWARM OPTIMISATION (PSO); SWARM INTELLIGENCE;

GLOBAL OPTIMIZATION;

EID: 34250847063     PISSN: 17518822     EISSN: None     Source Type: Journal    
DOI: 10.1049/iet-smt:20060124     Document Type: Article

References (22)

1. Di Barba, P., Gottvald, A., and Savini, A.: ' Global optimization of Loney's solenoid: a benchmark problem ', Int. J. Appl. Electromagn. Mech., 1995, 6, (4), p. 273-276 1383-5416
2. Borghi, C.A., and Fabbri, M.: ' Loney's solenoid multi-objective optimization problem ', IEEE Trans. Magn., 1999, 35, (3), p. 1706-1709 0018-9464
3. Cogotti, E., Fanni, A., and Pilo, F.: ' A comparison of optimization techniques for Loney's solenoids design: an alternative tabu search algorithm ', IEEE Trans. Magn., 2000, 36, (4), p. 1153-1157 0018-9464
4. Ciuprina, G., Ioan, D., and Munteanu, I.: ' Use of intelligent-particle swarm optimization in electromagnetics ', IEEE Trans. Magn., 2002, 38, (2), p. 1037-1040 10.1109/20.996266 0018-9464
5. Coelho, L.S., and Mariani, V.C.: ' Use of cultural particle swarm optimization for Loney's solenoid design ', Proc. 12th Biennial IEEE Conf. on Electromagnetic Field Computation, Miami, FL, USA, 2006, p. 482
6. Coelho, L.S., and Mariani, V.C.: ' Combining of differential evolution and implicit filtering algorithm applied to electromagnetic design optimization ', 11th, Online Conf. on Soft Computing in Industrial Applications, 2006, available online at: http://ssl.linklings.net/conferences/wsc11/
7. Protopescu, V., and Barhen, J.: ' Solving a class of continuous global optimization problems using quantum algorithms ', Phys. Lett. A, 2002, 296, (11), p. 9-14 0375-9601
8. Sun, J., Xu, W., and Feng, B.: ' A global search strategy of quantum-behaved particle swarm optimization ', Proc. IEEE Conf. on Cybernetics and Intelligent Systems, Singapore, p. 111-116
9. Shi, Y., and Eberhart, R.C.: ' Parameter selection in particle swarm optimizer ', Porto, V.W., Saravan, N., Waagen, D., Eiben, A.E., Proc. 7th Annual Conf. on Evolutionary Programming, (Springer-Verlag, Berlin, 1998), p. 591-601
10. Krohling, R.A., and Coelho, L.S.: ' Co-evolutionary particle swarm optimization using Gaussian distribution for solving constrained optimization problems ', IEEE Trans. Syst. Man Cybern. B, Cybern., 2006, 36, (6), p. 1407-1416 10.1109/TSMCB.2006.873185 1083-4419
11. Sun, J., Feng, B., and Xu, W.: ' Particle swarm optimization with particles having quantum behavior ', Proc. Congress on Evolutionary Computation, Portland, Oregon, USA, 2004, p. 325-331
12. Sun, J., Xu, W., and Feng, B.: ' Adaptive parameter control for quantum-behaved particle swarm optimization on individual level ', Proc. IEEE Int. Conf. on Systems, Man, and Cybernetics, Big Island, HI, USA, 2005, p. 3049-3054
13. Liu, J., Xu, W., and Sun, J.: ' Quantum-behaved particle swarm optimization with mutation operator ', Proc. 17th Int. Conf. on Tools with Artificial Intelligence, Hong Kong, China, 2005
14. Levin, F.S.: ' An introduction to quantum theory ', (Cambridge University Press, UK, 2002)
15. Kennedy, J.F., Eberhart, R.C., and Shi, Y.: ' Swarm intelligence ', (Morgan Kaufmann, San Francisco, CA, USA, 2001)
16. Secrest, B.R., and Lamont, G.B.: ' Visualizing particle swarm optimization-Gaussian particle swarm optimization ', Proc. IEEE Swarm Intelligence Symp., Indianapolis, IN, USA, 2003, p. 198-204
17. Higashi, N., and Iba, H.: ' Particle swarm optimization with Gaussian mutation ', Proc. IEEE Swarm Intelligence Symp., Indianapolis, IN, USA, 2003, p. 72-79
18. Krohling, R.A.: ' Gaussian swarm: a novel particle swarm optimization algorithm ', Proc. IEEE Conf. on Cybernetics and Intelligent Systems, Singapore, 2004, p. 372-376
19. Ratnaweera, A., Halgamuge, S.K., and Watson, H.C.: ' Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients ', IEEE Trans. Evol. Comput., 2004, 8, (3), p. 240-255 10.1109/TEVC.2004.826071 1089-778X
20. ' TEAM Benchmark Problem 22 ', 2006, available online at: http://www-igte.tu-graz.ac.at/team
21. Coelho, L.S., and Alotto, P.: ' Electromagnetic device optimization by hybrid evolution strategy approaches ', Proc. 9th Workshop on Optimization and Inverse Problems in Electromagnetism (OIPE 2006), Sorrento, Italy, 2006
22. Baumgartner, U., Magele, C., Preis, K., and Renhart, W.: ' Particle swarm optimisation for Pareto optimal solutions in electromagnetic shape design ', IEE Proc., Sci., Meas. Technol., 2004, 151, (6), p. 499-502 1350-2344