Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Parameter Selection in Particle Swarm Optimization
EP '98 Proceedings of the 7th International Conference on Evolutionary Programming VII
Evolutionary programming made faster
IEEE Transactions on Evolutionary Computation
Handling multiple objectives with particle swarm optimization
IEEE Transactions on Evolutionary Computation
An approach to multimodal biomedical image registration utilizing particle swarm optimization
IEEE Transactions on Evolutionary Computation
Dispersed particle swarm optimization
Information Processing Letters
Particle swarm optimization using lévy probability distribution
ISICA'07 Proceedings of the 2nd international conference on Advances in computation and intelligence
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Particle swarm optimization (PSO) is a new robust swarm intelligence technique, which has exhibited good performance on well-known numerical test problems. Though many improvements published aims to increase the computational efficiency, there are still many works need to do. Inspired by evolution programming theory, this paper proposes a new adaptive particle swarm optimization in which the velocity threshold dynamically changes during the course of a simulation. Seven benchmark functions are used to testify the new algorithm, and the results showed clearly the new adaptive PSO leads to a significantly better performance, although the performance improvements were found to be dependent on problems