Multi-Core Parallel Particle Swarm Optimization for the Operation of Inter-Basin Water Transfer-Supply Systems

Yong Peng, Anbang Peng (), Xiaoli Zhang, Huicheng Zhou, Lin Zhang, Wenzhong Wang and Zixin Zhang
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Yong Peng: Dalian University of Technology
Anbang Peng: Dalian University of Technology
Xiaoli Zhang: Dalian University of Technology
Huicheng Zhou: Dalian University of Technology
Lin Zhang: Dalian University of Technology
Wenzhong Wang: State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering
Zixin Zhang: Dalian University of Technology

Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), 2017, vol. 31, issue 1, No 3, 27-41

Abstract: Abstract 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.

Keywords: Inter-basin water transfer-supply systems; Multi-core; Parallel particle swarm optimization; Joint operation model; Fork/join framework (search for similar items in EconPapers)
Date: 2017
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Citations: View citations in EconPapers (9)

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DOI: 10.1007/s11269-016-1506-4

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