【摘要】 为在寻优过程中有效地保持算法的种群多样性,提出了一种改进的PSO(Particle Swarm Optimization)算法——PSOPC(Particle Swarm Optimizer based on Predator-prey Coevolution)。PSOPC算法将生态系统中捕食者和猎物的竞争协同进化机制嵌入到PSO算法中。基于PSOPC进行RFID(Radio Frequency IDentification)读写器网络调度模型的求解,根据读写器冲突关系的变化在线进行读写器的时隙分配求解与控制,在不影响读写器工作效率的同时,有效消除密集读写器环境下的读写器冲突问题,并优化整个读写器网络的工作效率。更多还原

【Abstract】 In order to improve PSOs performance on complex engineering problems,it presents a variant of PSO(Particle Swarm Optimization) called PSOPC(Particle Swarm Optimizer based on Predator-prey Coevolution),which takes into account the predator-prey behavior therefore high species diversity can be maintained as the whole population evolves.PSOPC is then applied to schedule RFID(Radio Frequency Identification) networks by assigning time slot to RFID readers on-line whereby reader collision can be minimized to ensure the current operation of the RFID system.Simulation results demonstrate that the PSOPC algorithm is more feasible and efficient than PSO in solving this real-world problem.更多还原