New ideas in optimization
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Population structure and particle swarm performance
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
A lifecycle model for simulating bacterial evolution
Neurocomputing
No free lunch theorems for optimization
IEEE Transactions on Evolutionary Computation
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
The fully informed particle swarm: simpler, maybe better
IEEE Transactions on Evolutionary Computation
Self-organizing hierarchical particle swarm optimizer with time-varying acceleration coefficients
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
Learning to play games using a PSO-based competitive learning approach
IEEE Transactions on Evolutionary Computation
An approach to multimodal biomedical image registration utilizing particle swarm optimization
IEEE Transactions on Evolutionary Computation
Comprehensive learning particle swarm optimizer for global optimization of multimodal functions
IEEE Transactions on Evolutionary Computation
Particle swarm optimizer based on small-world topology and comprehensive learning
ICIC'10 Proceedings of the 6th international conference on Advanced intelligent computing theories and applications: intelligent computing
Small-world particle swarm optimization with topology adaptation
Proceedings of the 15th annual conference on Genetic and evolutionary computation
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In this paper, a novel dynamic neighborhood topology based on small world network (SWLPSO) is introduced. The strategy of the learning exemplar choice of the particle is based upon the clustering coefficient and the average shortest distance. This strategy enables the diversity of the swarm to be preserved to discourage premature convergence. Experiments were conducted on a set of classical benchmark functions. The results demonstrate good performance in solving multimodal problems used in this paper when compared with the other PSO variants.