Human behavior-based particle swarm optimization

The Scientific World Journal

Volumn 2014, Issue , 2014, Pages

  Liu, Hao ^a,b   Xu, Gang ^c   Ding, Gui Yan ^b   Sun, Yu Bo ^b  

^a BEIJING INSTITUTE OF TECHNOLOGY   (China)

^b UNIVERSITY OF SCIENCE AND TECHNOLOGY LIAONING   (China)

^c NANCHANG UNIVERSITY   (China)

Author keywords

[No Author keywords available]

Indexed keywords

ACCELERATION; ALGORITHM; ARTICLE; BEHAVIOR; CONTROLLED STUDY; EXPERIMENTAL STUDY; EXPLORATORY BEHAVIOR; HUMAN; INFORMATION PROCESSING; MATHEMATICAL ANALYSIS; NORMAL DISTRIBUTION; PARTICLE SWARM OPTIMIZATION; SOCIAL STATUS; VELOCITY; ARTIFICIAL INTELLIGENCE; ORGANIZATION AND MANAGEMENT; PROCEDURES; QUALITY CONTROL; STATISTICS; THEORETICAL MODEL;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; BEHAVIOR; BENCHMARKING; EFFICIENCY, ORGANIZATIONAL; HUMANS; MODELS, THEORETICAL; STATISTICS AS TOPIC;

EID: 84900000785     PISSN: None     EISSN: 1537744X     Source Type: Journal    
DOI: 10.1155/2014/194706     Document Type: Article

References (31)

1. Kennedy J., Eberhart R., Particle swarm optimization. Proceedings of the IEEE International Conference on Neural Networks December 1995 1942 1948 2-s2.0-0029535737
2. Shi Y., Eberhart R., Modified particle swarm optimizer. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC '98) May 1998 69 73 2-s2.0-0031700696
3. Shi Y., Eberhart R. C., Fuzzy adaptive particle swarm optimization. Proceedings of the Congress on Evolutionary Computation May 2001 101 106 2-s2.0-0034869626
4. Eberhart R. C., Shi Y., Tracking and optimizing dynamic systems with particle swarms. Proceedings of the Congress on Evolutionary Computation May 2001 94 100 2-s2.0-0034870045
5. Xu G., An adaptive parameter tuning of particle swarm optimization algorithm. Applied Mathematics and Computation 2013 219 9 4560 4569 10.1016/j.amc.2012.10.067 MR3001505
6. Ratnaweera A., Halgamuge S. K., Watson H. C., Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients. IEEE Transactions on Evolutionary Computation 2004 8 3 240 255 2-s2.0-3142768423 10.1109/TEVC.2004.826071
7. Clerc M., Kennedy J., The particle swarm-explosion, stability, and convergence in a multidimensional complex space. IEEE Transactions on Evolutionary Computation 2002 6 1 58 73 2-s2.0-0036464756 10.1109/4235.985692
8. Eberhart R. C., Shi Y., Comparing inertia weights and constriction factors in particle swarm optimization. Proceedings of the Congress on Evolutionary Computation (CEC '00) July 2000 84 88 2-s2.0-0033666935
9. Angeline P. J., Using selection to improve particle swarm optimization. Proceedings of the IEEE International Conference on Evolutionary Computation (ICEC '98) May 1998 84 89 2-s2.0-0031697317
10. Chen Y.-P., Peng W.-C., Jian M.-C., Particle swarm optimization with recombination and dynamic linkage discovery. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 2007 37 6 1460 1470 2-s2.0-36749051693 10.1109/TSMCB.2007.904019
11. Andrews P. S., An investigation into mutation operators for particle swarm optimization. Proceedings of the IEEE Congress on Evolutionary Computation (CEC '06) July 2006 1044 1051 2-s2.0-34547336486
12. Zhang W.-J., Xie X.-F., DEPSO: Hybrid particle swarm with differential evolution operator. Proceedings of the IEEE International Conference on System Security and Assurance October 2003 3816 3821 2-s2.0-0242552409
13. Kiran M. S., Gündüz M., Baykan K., A novel hybrid algorithm based on particle swarm and ant colony optimization for finding the global minimum. Applied Mathematics and Computation 2012 219 4 1515 1521 10.1016/j.amc.2012.06.078 MR2983859
14. Liang J. J., Suganthan P. N., Dynamic multi-swarm particle swarm optimizer with local search. Proceedings of the IEEE Congress on Evolutionary Computation (CEC '05) September 2005 522 528 2-s2.0-27144442023
15. Kennedy J., Small worlds and mega-minds: effects of neighborhood topology on particle swarm performance. Proceedings of IEEE Congress on Evolutionary Computation 1999 1931 1938
16. Kennedy J., Mendes R., Population structure and particle swarm performance. Proceedings of the IEEE Congress on Evolutionary Computation 2002 1671 1676
17. Kennedy J., Bare bones particle swarms. Proceedings of the IEEE Swarm Intelligence Symposium 2003 80 87
18. Krohling R. A., Mendel E., Bare bones particle swarm optimization with Gaussian or cauchy jumps. Proceedings of the IEEE Congress on Evolutionary Computation (CEC '09) May 2009 3285 3291 2-s2.0-70449983741 10.1109/CEC.2009. 4983361
19. Omran M. G. H., Engelbrecht A. P., Salman A., Bare bones differential evolution. European Journal of Operational Research 2009 196 1 128 139 2-s2.0-56549114142 10.1016/j.ejor.2008.02.035
20. Sun J., Fang W., Palade V., Wu X., Xu W., Quantum-behaved particle swarm optimization with Gaussian distributed local attractor point. Applied Mathematics and Computation 2011 218 7 3763 3775 2-s2.0-80054982433 10.1016/j.amc.2011.09.021
21. Sun J., Wu X., Palade V., Fang W., Lai C.-H., Xu W., Convergence analysis and improvements of quantum-behaved particle swarm optimization. Information Sciences 2012 193 81 103 2-s2.0-84857788079 10.1016/j.ins.2012.01.005
22. Zhan Z.-H., Zhang J., Li Y., Chung H. S.-H., Adaptive particle swarm optimization. IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics 2009 39 6 1362 1381 2-s2.0-70349626031 10.1109/TSMCB.2009.2015956
23. Wang H., Sun H., Li C., Rahnamayan S., Pan J.-S., Diversity enhanced particle swarm optimization with neighborhood search. Information Sciences 2013 223 119 135 10.1016/j.ins.2012.10.012 MR2998556
24. Liang J. J., Qin A. K., Suganthan P. N., Baskar S., Comprehensive learning particle swarm optimizer for global optimization of multimodal functions. IEEE Transactions on Evolutionary Computation 2006 10 3 281 295 2-s2.0-33744730797 10.1109/TEVC.2005.857610
25. Juang Y.-T., Tung S.-L., Chiu H.-C., Adaptive fuzzy particle swarm optimization for global optimization of multimodal functions. Information Sciences 2011 181 20 4539 4549 2-s2.0-79960560056 10.1016/j.ins.2010.11.025
26. Salomon R., Re-evaluating genetic algorithm performance under coordinate rotation of benchmark functions. A survey of some theoretical and practical aspects of genetic algorithms. BioSystems 1996 39 3 263 278 2-s2.0-0029768771 10.1016/0303-2647(96)01621-8
27. Kennedy J., Mendes R., Neighborhood topologies in fully informed and bestof-neighborhood particle swarms. IEEE Transactions on Systems, Man, and Cybernetics, Part C 2006 36 4 515 519
28. Mendes R., Kennedy J., Neves J., The fully informed particle swarm: Simpler, maybe better. IEEE Transactions on Evolutionary Computation 2004 8 3 204 210 2-s2.0-3142781923 10.1109/TEVC.2004.826074
29. Liang J. J., Suganthan P. N., Dynamic multi-swarm particle swarm optimizer. Proceedings of the IEEE Swarm Intelligence Symposium (SIS '05) June 2005 127 132 2-s2.0-33745789624 10.1109/SIS.2005.1501611
30. Pant M., Radha T., Singh V. P., A new particle swarm optimization with quadratic interpolation. Proceedings of the International Conference on Computational Intelligence and Multimedia Applications (ICCIMA '07) December 2007 55 60 2-s2.0-41149086866 10.1109/ICCIMA.2007.24
31. Parsopoulos K. E., Vrahatis M. N., UPSO: a unified particle swarm scheme. Proceedings of the International Conference of Computational Methods in Sciences and Engineering 2004 1 868 873 Lecture Series on Computer and Computational Sciences