Experimental analysis of bound handling techniques in particle swarm optimization

IEEE Transactions on Evolutionary Computation

Volumn 17, Issue 2, 2013, Pages 259-271

  Helwig, Sabine ^a   Branke, Juergen ^b   Mostaghim, Sanaz ^c  

^a UNIVERSITY OF ERLANGEN NUREMBERG   (Germany)

^b UNIVERSITY OF WARWICK   (United Kingdom)

^c KARLSRUHE INSTITUTE OF TECHNOLOGY   (Germany)

Author keywords

Constrained optimization; particle swarm optimization (PSO)

Indexed keywords

ALGORITHM PERFORMANCE; BOUNDED SEARCH; EXPERIMENTAL ANALYSIS; HANDLING TECHNIQUE; OPTIMIZATION PROBLEMS; SEARCH BIAS; TEST PROBLEM;

CONSTRAINED OPTIMIZATION;

PARTICLE SWARM OPTIMIZATION (PSO);

EID: 84875717817     PISSN: 1089778X     EISSN: None     Source Type: Journal    
DOI: 10.1109/TEVC.2012.2189404     Document Type: Article

References (29)

1. K. Parsopoulos and M. Vrahatis, "Recent approaches to global optimization problems through particle swarm optimization," Natural Comput., vol. 1, nos. 2-3, pp. 235-306, Jun. 2002.
2. M. Clerc, Particle Swarm Optimization. London, U.K.: ISTE, 2006.
3. J. Kennedy and R. C. Eberhart, Swarm Intelligence. San Francisco, CA: Morgan Kaufmann, 2001.
4. Y. del Valle, G. K. Venayagamoorthy, S. Mohagheghi, J.-C. Hernandez, and R. G. Harley, "Particle swarm optimization: Basic concepts, variants and applications in power systems," IEEE Trans. Evol. Comput., vol. 12, no. 2, pp. 171-195, Apr. 2008.
5. J. Onwunalu and L. Durlofsky, "Application of a particle swarm optimization algorithm for determining optimum well location and type," Comput. Geosci., vol. 14, no. 1, pp. 183-198, 2010.
6. D. Jeyakumar, T. Jayabarathi, and T. Raghunathan, "Particle swarm optimization for various types of economic dispatch problems," Int. J. Electr. Power Energy Syst., vol. 28, no. 1, pp. 36-42, Jan. 2006.
7. Z.-L. Gaing, "A particle swarm optimization approach for optimum design of PID controller in AVR system," IEEE Trans. Energy Convers., vol. 19, no. 2, pp. 384-391, Jun. 2004.
8. S. Helwig and R. Wanka, "Particle swarm optimization in high-dimensional bounded search spaces," in Proc. IEEE Swarm Intell. Symp., Apr. 2007, pp. 198-205.
9. S. Helwig and R. Wanka, "Theoretical analysis of initial particle swarm behavior," in Proc. 10th Int. Conf. PPSN, Sep. 2008, pp. 889-898.
10. C. Coello Coello, "Theoretical and numerical constraint-handling techniques used with evolutionary algorithms: A survey of the state of the art," Comput. Methods Appl. Mech. Eng., vol. 191, no. 11, pp. 1245-1287, 2002.
11. Z. Michalewicz, "A survey of constraint handling techniques in evolutionary computation methods," in Proc. 4th Annu. Conf. Evol. Programming, 1995, pp. 135-155.
12. S. Janson and M. Middendorf, "A hierarchical particle swarm optimizer for dynamic optimization problems," in Applications of Evolutionary Computing (LNCS, vol. 3005), G. R. Raidl, Ed. Berlin, Germany: Springer, 2004, pp. 513-524.
13. J. Kennedy and R. Mendes, "Population structure and particle swarm performance," in Proc. Congr. Evol. Comput., 2002, pp. 1671-1676.
14. M. Clerc and J. Kennedy, "The particle swarm: Explosion, stability, and convergence in a multidimensional complex space," IEEE Trans. Evol. Comput., vol. 6, no. 1, pp. 58-73, Feb. 2002.
15. D. Bratton and J. Kennedy, "Defining a standard for particle swarm optimization," in Proc. IEEE Swarm Intell. Symp., Apr. 2007, pp. 120-127.
16. G. T. Pulido and C. A. Coello Coello, "A constraint-handling mechanism for particle swarm optimization," in Proc. CEC, Jun. 2004, pp. 1396-1403.
17. S. Mostaghim, W. E. Halter, and A. Wille, "Linear multiobjective particle swarm optimization," in Stigmergy Optimization (Computational Science, vol. 31), A. Abraham, C. Grosan, and V. Ramos, Eds. Berlin, Germany: Springer-Verlag, Jul. 2006, ch. 9, pp. 209-237.
18. B. Bochenek and P. Foryś, "Structural optimization for post-buckling behavior using particle swarms," Structural Multidisciplinary Optimization, vol. 32, no. 6, pp. 521-531, 2006.
19. M. Clerc. (2006). Confinements and Biases in Particle Swarm Optimization [Online]. Available: http://clerc.maurice.free.fr/pso
20. J. E. Alvarez-Benitez, R. M. Everson, and J. E. Fieldsend, "A MOPSO algorithm based exclusively on Pareto dominance concepts," in Proc. EMO, LNCS. 2005, pp. 459-473.
21. W.-J. Zhang, X.-F. Xie, and D.-C. Bi, "Handling boundary constraints for numerical optimization by particle swarm flying in periodic search space," in Proc. IEEE Congr. Evol. Comput., Jun. 2004, vol. 2, pp. 2307-2311.
22. D. Bratton and J. Kennedy, "Defining a standard for particle swarm optimization," in Proc. IEEE Swarm Intell. Symp., Apr. 2007, pp. 120-127.
23. R. C. Eberhart and Y. Shi, "Comparing inertia weights and constriction factors in particle swarm optimization," in Proc. Congr. Evol. Comput., 2000, pp. 84-88.
24. M. Clerc et al. (2007). Standard PSO [Online]. Available: http://www.particleswarm.info
25. R. C. Eberhart and J. Kennedy, "A new optimizer using particle swarm theory," in Proc. 6th Int. Symp. Micro Mach. Hum. Sci., 1995, pp. 39-43.
26. R. Mendes, "Population topologies and their influence in particle swarm performance," Ph.D. dissertation, Dept. Informática, Escola Engenharia, Univ. Minho, Braga, Portugal, 2004.
27. J. Kennedy and R. Mendes, "Population structure and particle swarm performance," in Proc. IEEE Congr. Evol. Comput., May 2002, pp. 1671-1676.
28. A. Owen and I. Harvey, "Adapting particle swarm optimization for fitness landscapes with neutrality," in Proc. IEEE Swarm Intell. Symp., Apr. 2007, pp. 258-265.
29. P. N. Suganthan, N. Hansen, J. J. Liang, K. Deb, Y. Chen, A. Auger, and S. Tiwari, "Problem definitions and evaluation criteria for the CEC 2005 special session on real-parameter optimization," Nanyang Technol. Univ., Singapore, KanGAL Rep. 2005005, 2005.