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Integrated Modeling of Multi-Type Blocks Storage Yards in Shipyard for Logistics Analysis

Published: 01 February 2021 Publication History

Abstract

This paper analyzes the process of ship blocks' transfers and temporary storages and proposes a method of multi-type blocks storage yards in a shipyard for logistics analysis to accurately assess the feasibility and difficulty of block transfers by constructing two modified directed graphs of all storage cells of a shipyard. Compared with the existing modeling methods, the proposed modeling method obtains transfer paths with feasible turnings and allows blocks' temporary storages within the shipyard's all storage yards rather than only one particular storage yard. It may improve the modeling accuracy by considering more details and offer more choices for logistics dispatcher.

References

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TAO N-R. Research on Resource Scheduling Problems during Ship Block Assembly Process [D]; Shanghai Jiaotong University, 2013.
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CHEN J, TIAN L, LIU S, et al. HMM-based Method for Detection of Ship Block Unproductive Transfer. unpublished,
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PARK C, SEO J, KIM J, et al. Assembly block storage location assignment at a shipyard: a case of Hyundai Heavy Industries [J]. Production Planning & Control, 2007, 18(3): 180--9.
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PARK C, SEO J. Assembly block storage location assignment problem: revisited [J]. Production Planning & Control, 2009, 20(3): 216--26.
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ZHANG Z Y, SHEN G, LIU X R, et al. Block storage yard scheduling of shipbuilding based on shortest-path algorithm [J]. Computer Integrated Manufacturing Systems, 2012, 18(9): 1982--90.
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ZHANG Z-Y, XU J-X, JI F. Shipbuilding Yard Scheduling Approach Based on Genetic Algorithm [J]. Journal of Shanghai Jiao Tong University, 2013, 47(7): 1037--43.
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ZHANG Z-Y, JI F, ZENG J-Z. Block stockyard scheduling approach based on an improved genetic algorithm [J]. Journal of Harbin Engineering University, 2015, 36(8): 1103--8.
[8]
ZENG J-Z, ZHANG Z-Y. Block stockyard scheduling and optimizing based on an intelligent algorithm [J]. Journal of Harbin Engineering University, 2016, 37(1): 42--8.
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ZHANG Z-Y, ZENG J-Z. Obstructive block stockyard scheduling and optimization based on heuristic rules [J]. Journal of Harbin Engineering University, 2016, 37(10): 1417--26.
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ZENG J-Z, ZHANG Z-Y, XING Y, et al. Block storage yard scheduling of shipbuilding based on shortest-path algorithm [J]. Computer Integrated Manufacturing Systems, 2016, 22(9): 2166--75.
[11]
MENG L-T, JIANG Z-H, TAO N-R, et al. Multi-Stockyard Scheduling Considering Technological Process and Combined Assembly Block [J]. Journal of Shanghai Jiaotong University, 2020, 54(4): 331--43.
[12]
MENG L-T, JIANG Z-H, TAO N-R, et al. Combined Assembly Block Scheduling in Storage Yard of Shipbuilding [J]. Journal of shanghai jiaotong university, 2019, 53(7): 780--8.

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  1. Integrated Modeling of Multi-Type Blocks Storage Yards in Shipyard for Logistics Analysis

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      EITCE '20: Proceedings of the 2020 4th International Conference on Electronic Information Technology and Computer Engineering
      November 2020
      1202 pages
      ISBN:9781450387811
      DOI:10.1145/3443467
      Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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      Association for Computing Machinery

      New York, NY, United States

      Publication History

      Published: 01 February 2021

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      Author Tags

      1. integrated modeling
      2. modified directed graph
      3. multi-type storage yards
      4. ship block
      5. transfer

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      EITCE 2020

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      EITCE '20 Paper Acceptance Rate 214 of 441 submissions, 49%;
      Overall Acceptance Rate 508 of 972 submissions, 52%

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