个人信息Personal Information
教授
博士生导师
硕士生导师
性别:男
毕业院校:大连理工大学
学位:博士
所在单位:水利工程系
学科:水文学及水资源. 工程管理
办公地点:实验3#-435
联系方式:电话:13804245837 QQ:2246578293 微信:dutwaterzhou
电子邮箱:hczhou@dlut.edu.cn
Multi-Core Parallel Particle Swarm Optimization for the Operation of Inter-Basin Water Transfer-Supply Systems
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论文类型:期刊论文
发表时间:2017-01-01
发表刊物:WATER RESOURCES MANAGEMENT
收录刊物:SCIE、EI、Scopus
卷号:31
期号:1
页面范围:27-41
ISSN号:0920-4741
关键字:Inter-basin water transfer-supply systems; Multi-core; Parallel particle swarm optimization; Joint operation model; Fork/join framework
摘要:To optimize the joint operation model for inter-basin water transfer-supply systems (IBWTS), this study proposes three multi-core parallel particle swarm optimization (PPSO) algorithms (i.e., PPSO_ring, PPSO_star, PPSO_share). These algorithms are based on the Fork/Join framework and the concurrency in Java. The biggest difference between the proposed PPSOs and the traditional one, which is also based on the Fork/Join framework, is that the former can exchange information among the threads (sub-swarms), while the latter cannot. To implement the proposed PPSOs, the Fork/Join framework is used to assign threads to different CPU cores, thereby evolving the standard PSO separately, and the synchronization-and-communication mechanisms of concurrency in Java is used to exchange information among the threads. The North-line IBWTS in Liaoning Province of China is taken as a case study to test the proposed algorithms. The analysis of the algorithms demonstrate that all the three proposed PPSOs outperform the traditional one, which indicates that information exchange among the sub-swarms can improve algorithm performance. PPSO_share performs better than PPSO_ring and PPSO_star, which illustrates that when each sub-swarm's best particle, the particle's best position and the best particle of the whole swarm are used to update the particle's velocity, the algorithm performance can be further improved. The operation results show that PPSO_share can take full advantage of multi-core resources and enhance the computing efficiency and solution accuracy of the joint operation model, showing its potential practicability and validity for complex multi-reservoir system operations in the future.