IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0265047.html
   My bibliography  Save this article

Scheduling management and optimization analysis of intermediate products transfer in a shipyard for cruise ships

Author

Listed:
  • Jiajie Liu
  • Jingbo Yin
  • Rafi Ullah Khan

Abstract

Shipbuilding is a complex and large-scale operation involving many intermediate products (blocks) and the frequent transfer of blocks among workshops and stockyards. The reasonable use of methods to complete the transfer scheduling of intermediate products is of great importance. In this paper, the blocks and the flat transporters are the research objects. Based on organizing the various logistical processes for blocks and the circulation process in the shipyard, we established a model that takes the task time window and other factors as constraints, and minimizes the sum of delay time and no-load time of flat transporters while satisfying the punctuality of scheduling tasks. Three conclusions are reached: (1)The flat transporter utilization rate is inversely related to the value of the objective function. The smaller the value of the objective function, the more the usage rate of a particular one (2) loading is the biggest obstacle to the overall working time of flat transporters, and a simple optimization model cannot solve this problem; and (3) based on the optimization model, the load efficiency of flat transporters can be improved, and the delivery time can be reduced.

Suggested Citation

  • Jiajie Liu & Jingbo Yin & Rafi Ullah Khan, 2022. "Scheduling management and optimization analysis of intermediate products transfer in a shipyard for cruise ships," PLOS ONE, Public Library of Science, vol. 17(3), pages 1-20, March.
    • Handle: RePEc:plo:pone00:0265047
    DOI: 10.1371/journal.pone.0265047
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0265047
    Download Restriction: no
    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0265047&type=printable
    Download Restriction: no
    File URL: https://libkey.io/10.1371/journal.pone.0265047?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Sana Jawarneh & Salwani Abdullah, 2015. "Sequential Insertion Heuristic with Adaptive Bee Colony Optimisation Algorithm for Vehicle Routing Problem with Time Windows," PLOS ONE, Public Library of Science, vol. 10(7), pages 1-23, July.
    2. Park, Jaehun & Lee, Dongha & Zhu, Joe, 2014. "An integrated approach for ship block manufacturing process performance evaluation: Case from a Korean shipbuilding company," International Journal of Production Economics, Elsevier, vol. 156(C), pages 214-222.
    3. Valls, Vicente & Ballestin, Francisco & Quintanilla, Sacramento, 2008. "A hybrid genetic algorithm for the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 185(2), pages 495-508, March.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Shahsavar, Aria & Sadeghi, J. Kiarash & Shockley, Jeff & Ojha, Divesh, 2021. "On the relationship between lean scheduling and economic performance in shipbuilding: A proposed model and comparative evaluation," International Journal of Production Economics, Elsevier, vol. 239(C).
    2. Pfeifer, Jeremy & Barker, Kash & Ramirez-Marquez, Jose E. & Morshedlou, Nazanin, 2015. "Quantifying the risk of project delays with a genetic algorithm," International Journal of Production Economics, Elsevier, vol. 170(PA), pages 34-44.
    3. Yang-Kuei Lin & Chin Soon Chong, 2017. "Fast GA-based project scheduling for computing resources allocation in a cloud manufacturing system," Journal of Intelligent Manufacturing, Springer, vol. 28(5), pages 1189-1201, June.
    4. Piran, Fabio Antonio Sartori & Lacerda, Daniel Pacheco & Camargo, Luis Felipe Riehs & Viero, Carlos Frederico & Dresch, Aline & Cauchick-Miguel, Paulo Augusto, 2016. "Product modularization and effects on efficiency: An analysis of a bus manufacturer using data envelopment analysis (DEA)," International Journal of Production Economics, Elsevier, vol. 182(C), pages 1-13.
    5. Vanhoucke, Mario & Coelho, José, 2016. "An approach using SAT solvers for the RCPSP with logical constraints," European Journal of Operational Research, Elsevier, vol. 249(2), pages 577-591.
    6. Yang, Zaoli & Shang, Wen-Long & Zhang, Haoran & Garg, Harish & Han, Chunjia, 2022. "Assessing the green distribution transformer manufacturing process using a cloud-based q-rung orthopair fuzzy multi-criteria framework," Applied Energy, Elsevier, vol. 311(C).
    7. Zhenyuan Liu & Lei Xiao & Jing Tian, 2016. "An activity-list-based nested partitions algorithm for resource-constrained project scheduling," International Journal of Production Research, Taylor & Francis Journals, vol. 54(16), pages 4744-4758, August.
    8. Liu, Jiawen & Gong, Yeming (Yale) & Zhu, Joe & Zhang, Jinlong, 2018. "A DEA-based approach for competitive environment analysis in global operations strategies," International Journal of Production Economics, Elsevier, vol. 203(C), pages 110-123.
    9. Barbosa, Luziane Machado & Lacerda, Daniel Pacheco & Piran, Fabio Antonio Sartori & Dresch, Aline, 2017. "Exploratory analysis of the variables prevailing on the effects of product modularization on production volume and efficiency," International Journal of Production Economics, Elsevier, vol. 193(C), pages 677-690.
    10. Song Wang & Caizhi Sun & Xin Li & Wei Zou, 2016. "Sustainable Development in China’s Coastal Area: Based on the Driver-Pressure-State-Welfare-Response Framework and the Data Envelopment Analysis Model," Sustainability, MDPI, vol. 8(9), pages 1-19, September.
    11. Yangkun Xia & Zhuo Fu & Lijun Pan & Fenghua Duan, 2018. "Tabu search algorithm for the distance-constrained vehicle routing problem with split deliveries by order," PLOS ONE, Public Library of Science, vol. 13(5), pages 1-19, May.
    12. Sungmin Park & Pansoo Kim, 2021. "Operational Performance Evaluation of Korean Ship Parts Manufacturing Industry Using Dynamic Network SBM Model," Sustainability, MDPI, vol. 13(23), pages 1-20, November.
    13. Longlong Leng & Jingling Zhang & Chunmiao Zhang & Yanwei Zhao & Wanliang Wang & Gongfa Li, 2020. "A novel bi-objective model of cold chain logistics considering location-routing decision and environmental effects," PLOS ONE, Public Library of Science, vol. 15(4), pages 1-29, April.
    14. Fündeling, C.-U. & Trautmann, N., 2010. "A priority-rule method for project scheduling with work-content constraints," European Journal of Operational Research, Elsevier, vol. 203(3), pages 568-574, June.
    15. Peteghem, Vincent Van & Vanhoucke, Mario, 2010. "A genetic algorithm for the preemptive and non-preemptive multi-mode resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 201(2), pages 409-418, March.
    16. Tseng, Lin-Yu & Lin, Ya-Tai, 2010. "A hybrid genetic algorithm for no-wait flowshop scheduling problem," International Journal of Production Economics, Elsevier, vol. 128(1), pages 144-152, November.
    17. Siqing Shan & Zhongjun Hu & Zhilian Liu & Jihong Shi & Li Wang & Zhuming Bi, 2017. "An adaptive genetic algorithm for demand-driven and resource-constrained project scheduling in aircraft assembly," Information Technology and Management, Springer, vol. 18(1), pages 41-53, March.
    18. Fabio Antonio Sartori Piran & Alaércio De Paris & Daniel Pacheco Lacerda & Luis Felipe Riehs Camargo & Rosiane Serrano & Ricardo Augusto Cassel, 2020. "Overall Equipment Effectiveness: Required but not Enough—An Analysis Integrating Overall Equipment Effect and Data Envelopment Analysis," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 21(2), pages 191-206, June.
    19. Hongbo Li & Erik Demeulemeester, 2016. "A genetic algorithm for the robust resource leveling problem," Journal of Scheduling, Springer, vol. 19(1), pages 43-60, February.
    20. Moumene, Khaled & Ferland, Jacques A., 2009. "Activity list representation for a generalization of the resource-constrained project scheduling problem," European Journal of Operational Research, Elsevier, vol. 199(1), pages 46-54, November.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0265047. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.