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LI Bin. Hierarchical, parallel, heterogeneous and reconfigurable computation model of container terminal handling system[J]. Journal of Traffic and Transportation Engineering, 2019, 19(2): 136-155. doi: 10.19818/j.cnki.1671-1637.2019.02.013
Citation: LI Bin. Hierarchical, parallel, heterogeneous and reconfigurable computation model of container terminal handling system[J]. Journal of Traffic and Transportation Engineering, 2019, 19(2): 136-155. doi: 10.19818/j.cnki.1671-1637.2019.02.013
shu

Hierarchical, parallel, heterogeneous and reconfigurable computation model of container terminal handling system

doi: 10.19818/j.cnki.1671-1637.2019.02.013

  • School of Transportation, Fujian University of Technology, Fuzhou 350118, Fujian, China

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  • Author Bio:

    LI Bin (1979-), male, professor, PhD, mse2007_lb@whut.edu.cn

  • Received Date: 2018-09-25
  • Publish Date: 2019-04-25
    Abstract
  • Based on computational thinking and computational lens, the loading and unloading operations and the scheduling decisions of container terminals were analyzed. Based on the parallel computation, heterogeneous computation and reconfigurable computation, a hierarchical, parallel, heterogeneous, and reconfigurable computation model of container terminal handling (HPHRCM-CTH) from the perspective of computation logistics was proposed. The design philosophies and operational mechanisms of typical computing architectures in the computer science were generalized, migrated, modified, fused, and customized to the container terminal handling system (CTHS), and the hybrid scheduling strategy for the HPHRCM-CTH was presented. A new abstract computation model and engineering solution to the container terminal scheduling were put forward. Taking a large container terminal as an example, the design and performance evaluation of logistics generalized computation automation were carried out based on the HPHRCM-CTH. Analysis result shows that the HPHRCM-CTH can determine the upper limit of container throughput that is about 2.75 times of the annual design capacity of the container terminal in the example. At the condition of full load, the scheduling strategies of load balancing for the pending queues of containers (LB-PQC) and ship types (LB-PQS) can shorten the logistics generalized computation task latency (LGC-TL) of large container mainline ships by about 17 h. At the condition of obvious job overload, the LB-PQC can reduce the LGC-TL by 100-110 h, while the LB-PQS can reduce the LGC-TL by about 120 h. At the conditions of full load and job overload, the LB-PQC and LB-PQS can reduce the logistics generalized computation memory access time (LGC-MAT) for large container mainline ships by 1-2 h, and the LB-PQS performs better under the conditions of job overload. The LB-PQC and LB-PQS both can give well priority to the key service liners, and have the respective applicable condition and scheduling emphasis, and the terminal manager can choose the right one according to the specific situation.

     

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