IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v244y2016i1d10.1007_s10479-014-1741-0.html
   My bibliography  Save this article

A simple algorithm to evaluate supply-chain reliability for brittle commodity logistics under production and delivery constraints

Author

Listed:
  • Yi-Kuei Lin

    (National Taiwan University of Science and Technology)

  • Cheng-Ta Yeh

    (Shih Hsin University)

  • Cheng-Fu Huang

    (National Taiwan University of Science and Technology)

Abstract

This paper focuses on developing a network model to evaluate supply-chain reliability for the brittle commodity logistics, in which the network is composed of branches and vertices. A vertex denotes a supplier, a transfer center, or a customer and a branch connecting a pair of vertices denotes a carrier. In the brittle commodity logistics network, each supplier has limited production capacity and the production cost is counted in terms of the number of the provided goods. Moreover, the delivery capacity (e.g. number of containers) provided by any carrier is multistate because the partial capacities may be reserved for other customers, and the delivery cost is counted in terms of the consumed delivery capacity. In the brittle commodity delivery, the goods may be damaged by natural disasters, traffic accidents, collisions, and so on, such that the intact goods can not satisfy the customer demand. Hence the delivery damage should be considered while evaluating the performance of a logistics network. This paper proposes the supply-chain reliability, which is defined as the probability of the network to successfully deliver goods to the customer with the delivery damage, limited production capacity, and budget considerations, to be a performance index. In terms of minimal paths, an algorithm is developed to evaluate the supply-chain reliability. A practical case of flat glass logistics is employed to discuss the management implications of the supply-chain reliability.

Suggested Citation

  • Yi-Kuei Lin & Cheng-Ta Yeh & Cheng-Fu Huang, 2016. "A simple algorithm to evaluate supply-chain reliability for brittle commodity logistics under production and delivery constraints," Annals of Operations Research, Springer, vol. 244(1), pages 67-83, September.
  • Handle: RePEc:spr:annopr:v:244:y:2016:i:1:d:10.1007_s10479-014-1741-0
    DOI: 10.1007/s10479-014-1741-0
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-014-1741-0
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.

    File URL: https://libkey.io/10.1007/s10479-014-1741-0?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2011. "Maximal network reliability for a stochastic power transmission network," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1332-1339.
    2. Nader Azad & Georgios Saharidis & Hamid Davoudpour & Hooman Malekly & Seyed Yektamaram, 2013. "Strategies for protecting supply chain networks against facility and transportation disruptions: an improved Benders decomposition approach," Annals of Operations Research, Springer, vol. 210(1), pages 125-163, November.
    3. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2010. "Optimal carrier selection based on network reliability criterion for stochastic logistics networks," International Journal of Production Economics, Elsevier, vol. 128(2), pages 510-517, December.
    4. Chopra, Sunil, 2003. "Designing the distribution network in a supply chain," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 39(2), pages 123-140, March.
    5. Lin, Yi-Kuei, 2007. "Performance evaluation for the logistics system in case that capacity weight varies from arcs and types of commodity," International Journal of Production Economics, Elsevier, vol. 107(2), pages 572-580, June.
    6. Lin, Yi-Kuei, 2010. "A stochastic model to study the system capacity for supply chains in terms of minimal cuts," International Journal of Production Economics, Elsevier, vol. 124(1), pages 181-187, March.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao, 2019. "Reliability of a stochastic intermodal logistics network under spoilage and time considerations," Annals of Operations Research, Springer, vol. 277(1), pages 95-118, June.
    2. Huang, Cheng-Hao & Lin, Yi-Kuei, 2024. "Rescue and safety system development and performance evaluation by network reliability," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    3. Yi-Feng Niu & Can He & De-Qiang Fu, 2022. "Reliability assessment of a multi-state distribution network under cost and spoilage considerations," Annals of Operations Research, Springer, vol. 309(1), pages 189-208, February.
    4. Amirmohsen Golmohammadi & Alireza Tajbakhsh & Mohamed Dia & Pawoumodom M. Takouda, 2022. "Effect of timing on reliability improvement and ordering decisions in a decentralized assembly system," Annals of Operations Research, Springer, vol. 312(1), pages 159-192, May.
    5. Jihai Zhang & Zhile Wang & Fan Ren, 2019. "Optimization of humanitarian relief supply chain reliability: a case study of the Ya’an earthquake," Annals of Operations Research, Springer, vol. 283(1), pages 1551-1572, December.

    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. Cheng-Ta Yeh & Yi-Kuei Lin & Cheng-Fu Huang, 2016. "Vehicle glass distribution reliability measurement under transportation cost constraint," European Journal of Industrial Engineering, Inderscience Enterprises Ltd, vol. 10(2), pages 243-263.
    2. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao, 2019. "Reliability of a stochastic intermodal logistics network under spoilage and time considerations," Annals of Operations Research, Springer, vol. 277(1), pages 95-118, June.
    3. Niu, Yi-Feng & Gao, Zi-You & Lam, William H.K., 2017. "Evaluating the reliability of a stochastic distribution network in terms of minimal cuts," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 100(C), pages 75-97.
    4. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2010. "Optimal carrier selection based on network reliability criterion for stochastic logistics networks," International Journal of Production Economics, Elsevier, vol. 128(2), pages 510-517, December.
    5. Cheng-Fu Huang, 2019. "Evaluation of system reliability for a stochastic delivery-flow distribution network with inventory," Annals of Operations Research, Springer, vol. 277(1), pages 33-45, June.
    6. Yi-Feng Niu & Can He & De-Qiang Fu, 2022. "Reliability assessment of a multi-state distribution network under cost and spoilage considerations," Annals of Operations Research, Springer, vol. 309(1), pages 189-208, February.
    7. Niu, Yi-Feng & Lam, William H.K. & Gao, Ziyou, 2014. "An efficient algorithm for evaluating logistics network reliability subject to distribution cost," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 67(C), pages 175-189.
    8. H. Khorshidian & M. Akbarpour Shirazi & S. M. T. Fatemi Ghomi, 2019. "An intelligent truck scheduling and transportation planning optimization model for product portfolio in a cross-dock," Journal of Intelligent Manufacturing, Springer, vol. 30(1), pages 163-184, January.
    9. Timo Gschwind & Stefan Irnich & Simon Emde & Christian Tilk, 2018. "Branch-Cut-and-Price for the Scheduling Deliveries with Time Windows in a Direct Shipping Network," Working Papers 1805, Gutenberg School of Management and Economics, Johannes Gutenberg-Universität Mainz.
    10. Eduardo Álvarez-Miranda & Jordi Pereira, 2021. "A Districting Application with a Quality of Service Objective," Mathematics, MDPI, vol. 10(1), pages 1-21, December.
    11. Bai, Guanghan & Zuo, Ming J. & Tian, Zhigang, 2015. "Search for all d-MPs for all d levels in multistate two-terminal networks," Reliability Engineering and System Safety, Elsevier, vol. 142(C), pages 300-309.
    12. Bhuiyan, Tanveer Hossain & Medal, Hugh R. & Harun, Sarah, 2020. "A stochastic programming model with endogenous and exogenous uncertainty for reliable network design under random disruption," European Journal of Operational Research, Elsevier, vol. 285(2), pages 670-694.
    13. Yeh, Wei-Chang & Chu, Ta-Chung, 2018. "A novel multi-distribution multi-state flow network and its reliability optimization problem," Reliability Engineering and System Safety, Elsevier, vol. 176(C), pages 209-217.
    14. Timo Gschwind & Stefan Irnich & Christian Tilk & Simon Emde, 2020. "Branch-cut-and-price for scheduling deliveries with time windows in a direct shipping network," Journal of Scheduling, Springer, vol. 23(3), pages 363-377, June.
    15. Scott DuHadway & Steven Carnovale & Benjamin Hazen, 2019. "Understanding risk management for intentional supply chain disruptions: risk detection, risk mitigation, and risk recovery," Annals of Operations Research, Springer, vol. 283(1), pages 179-198, December.
    16. Tianming Gao & Vasilii Erokhin & Aleksandr Arskiy, 2019. "Dynamic Optimization of Fuel and Logistics Costs as a Tool in Pursuing Economic Sustainability of a Farm," Sustainability, MDPI, vol. 11(19), pages 1-16, October.
    17. Cheng, Chun & Qi, Mingyao & Zhang, Ying & Rousseau, Louis-Martin, 2018. "A two-stage robust approach for the reliable logistics network design problem," Transportation Research Part B: Methodological, Elsevier, vol. 111(C), pages 185-202.
    18. Xiao, Hui & Shi, Daimin & Ding, Yi & Peng, Rui, 2016. "Optimal loading and protection of multi-state systems considering performance sharing mechanism," Reliability Engineering and System Safety, Elsevier, vol. 149(C), pages 88-95.
    19. Sheikh-Zadeh, Alireza & Rossetti, Manuel D. & Scott, Marc A., 2021. "Performance-based inventory classification methods for large-Scale multi-echelon replenishment systems," Omega, Elsevier, vol. 101(C).
    20. Hanieh Shekarabi & Mohammad Mahdi Vali-Siar & Ashkan Mozdgir, 2024. "Food supply chain network design under uncertainty and pandemic disruption," Operational Research, Springer, vol. 24(2), pages 1-37, June.

    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:spr:annopr:v:244:y:2016:i:1:d:10.1007_s10479-014-1741-0. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.