WANG Chao,QIAO Junfei.An parameter adaptive particle swarm optimization foroptimal design of water supply systems[J].CAAI Transactions on Intelligent Systems,2015,10(5):722-728.[doi:10.11992/tis.201410036]





An parameter adaptive particle swarm optimization foroptimal design of water supply systems
王超12 乔俊飞12
1. 北京工业大学 电子信息与控制工程学院, 北京 100124;
2. 北京工业大学 计算智能与智能系统北京市重点实验室, 北京 100124
WANG Chao12 QIAO Junfei12
1. College of Electronic Information and Control Engineering, Beijing University of Technology, Beijing 100124, China;
2. Beijing Key Laboratory of Computational Intelligence and Intelligence System, Beijing University of Technology, Beijing 100124, China
water supply systemparticle trajectoriessimilarityparameter adjustmentadaptive particle swarm op-timization
Particle swarm optimization easily falls into a local optimum when solving water supply optimization prob-lems. In order to solve this weakness, by analyzing particle trajectories and the similarity of particles, this paper proposes a parameter adaptive particle swarm optimization (PAPSO). By estimating the degree of similarity between particles and expected particles, the algorithm dynamically adjusts parameters and balances the global and local search ability. The algorithm uses the variation strategy of staging to increase the population diversity and ensure that it converges to the global optimum. The tower of Hanoi network and New York network have been optimized by the improved algorithm, and the result shows that the PAPSO algorithm can be effectively applied to the combinato-rial optimization of water supply pipeline networks. The proposed algorithm has been applied to optimize an actual pipe network reconstruction case and the result shows that the algorithm has better optimization and convergence performance.


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 MENG Qinchao,YANG Cuili,QIAO Junfei.Multi-objective optimization design of water distribution systems based on improved SPEA2 algorithm[J].CAAI Transactions on Intelligent Systems,2018,13(5):118.[doi:10.11992/tis.201701012]


更新日期/Last Update: 2015-11-16