Optimal multi-thresholding using a hybrid optimization approach
Pattern Recognition Letters
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 hybrid genetic algorithm and particle swarm optimization for multimodal functions
Applied Soft Computing
A hybridized approach to data clustering
Expert Systems with Applications: An International Journal
An effective hybrid PSO-based algorithm for flow shop scheduling with limited buffers
Computers and Operations Research
A new particle swarm optimization for the open shop scheduling problem
Computers and Operations Research
A particle swarm optimization algorithm for the multiple-level warehouse layout design problem
Computers and Industrial Engineering
WSEAS TRANSACTIONS on SYSTEMS
A new hybrid NM method and particle swarm algorithm for multimodal function optimization
IDA'05 Proceedings of the 6th international conference on Advances in Intelligent Data Analysis
Hybrid Particle Swarm Optimization With Wavelet Mutation and Its Industrial Applications
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Particle swarm optimization with selective particle regeneration for data clustering
Expert Systems with Applications: An International Journal
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This paper proposes an improved particle swarm optimization (PSO). In order to increase the efficiency, suggestions on parameter settings is made and a mechanism is designed to prevent particles fall into the local optimal. To evaluate its effectiveness and efficiency, this approach is applied to multimodal function optimizing tasks. 16 benchmark functions were tested, and results were compared with those of PSO, HNMPSO and GA-PSO. It shows the proposed method is both robust and suitable for multimodal function optimization.