Swarm intelligence
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Completely Derandomized Self-Adaptation in Evolution Strategies
Evolutionary Computation
Genetic Approach for Network Planning in the RFID Systems
ISDA '06 Proceedings of the Sixth International Conference on Intelligent Systems Design and Applications - Volume 02
Application of A Multi-Species Optimizer in Ubiquitous Computing for RFID Networks Scheduling
ICNC '07 Proceedings of the Third International Conference on Natural Computation - Volume 02
Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab
Evolutionary Intelligence: An Introduction to Theory and Applications with Matlab
The particle swarm - explosion, stability, and convergence in amultidimensional complex space
IEEE Transactions on Evolutionary Computation
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In this paper, we develop an optimization model for planning the positions of readers in the RFID network based on a novel Multi-swarm Particle Swarm Optimizer called PS2O. The main idea of PS2O is to extend the single population PSO to the interacting multi-swarms model by constructing hierarchical interaction topology and enhanced dynamical update equations. This algorithm, which is conceptually simple and easy to implement, has considerable potential for solving complex optimization problems. Simulation results show that the proposed PS2O algorithm proves to be superior for planning RFID networks than the standard PSO and other two evolutionary algorithms, namely Genetic Algorithm (GA) and Evolution Strategy (ES), in terms of optimization accuracy and computation robustness.