IDEAS home Printed from https://ideas.repec.org/a/spr/annopr/v346y2025i3d10.1007_s10479-025-06521-y.html
   My bibliography  Save this article

Optimal carrier selection to improve logistics network reliability with delivery spoilage

Author

Listed:
  • Yi-Feng Niu

    (Chongqing University of Posts and Telecommunications
    Chongqing University of Posts and Telecommunications)

  • Meng-Meng Yuan

    (Chongqing University of Posts and Telecommunications)

  • Xiu-Zhen Xu

    (Chongqing University of Posts and Telecommunications
    Chongqing University of Posts and Telecommunications)

Abstract

In a highly competitive market environment, outsourcing of logistics service is one of the most significant strategies for enterprises to enhance competitiveness. As a key component of logistics outsourcing, carrier selection directly affects logistics service quality. In general, there are multiple carriers to provide freight service along each route of a logistics network. Each carrier has stochastic capacity owing to that the carrier’s capacity may be partially occupied by other customers. Moreover, goods spoilage often occurs during transportation such that the amount of intact goods delivered may not fulfill the market demand. Thus, each carrier in this study is characterized by stochastic capacity that denotes freight capacity and delivery spoilage that denotes freight quality. Both freight capacity and freight quality are integrated into the carrier selection problem from the viewpoint of network reliability. An effective method that incorporates network reliability algorithm and genetic algorithm is developed to find the optimal carrier selection and the maximum network reliability. A practical logistics network is analyzed to showcase the utility of the algorithm in carrier selection, together with a sensitivity analysis to figure out the important carriers.

Suggested Citation

  • Yi-Feng Niu & Meng-Meng Yuan & Xiu-Zhen Xu, 2025. "Optimal carrier selection to improve logistics network reliability with delivery spoilage," Annals of Operations Research, Springer, vol. 346(3), pages 2195-2223, March.
    • Handle: RePEc:spr:annopr:v:346:y:2025:i:3:d:10.1007_s10479-025-06521-y
    DOI: 10.1007/s10479-025-06521-y
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s10479-025-06521-y
    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/s10479-025-06521-y?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. Liao, Zhiying & Rittscher, Jens, 2007. "A multi-objective supplier selection model under stochastic demand conditions," International Journal of Production Economics, Elsevier, vol. 105(1), pages 150-159, January.
    3. Yi-Kuei Lin & Cheng-Fu Huang & Cheng-Ta Yeh, 2016. "Assessment of system reliability for a stochastic-flow distribution network with the spoilage property," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(6), pages 1421-1432, April.
    4. 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.
    5. Liu, Tao & Bai, Guanghan & Tao, Junyong & Zhang, Yun-An & Fang, Yining & Xu, Bei, 2022. "Modeling and evaluation method for resilience analysis of multi-state networks," Reliability Engineering and System Safety, Elsevier, vol. 226(C).
    6. Niu, Yi-Feng & Zhao, Xia & Xu, Xiu-Zhen & Zhang, Shi-Yun, 2023. "Reliability assessment of a stochastic-flow distribution network with carbon emission constraint," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    7. 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.
    8. Yi-Kuei Lin & Cheng-Ta Yeh & Cheng-Fu Huang, 2017. "Reliability assessment of a multistate freight network for perishable merchandise with multiple suppliers and buyers," International Journal of Systems Science, Taylor & Francis Journals, vol. 48(1), pages 74-83, January.
    9. Peter Dzakah FANAM & Leigh ACKERLY, 2019. "Evaluating ocean carrier selection criteria: perspectives of Tasmanian shippers," Journal of Shipping and Trade, Springer, vol. 4(1), pages 1-16, December.
    10. Huang, Cheng-Hao & Huang, Ding-Hsiang & Lin, Yi-Kuei, 2023. "Network reliability prediction for random capacitated-flow networks via an artificial neural network," Reliability Engineering and System Safety, Elsevier, vol. 237(C).
    11. 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.
    12. Lin, Yi-Kuei & Yeh, Cheng-Ta, 2012. "Determining the optimal double-component assignment for a stochastic computer network," Omega, Elsevier, vol. 40(1), pages 120-130, January.
    13. Majid Forghani-elahabad & Nelson Kagan, 2019. "Reliability evaluation of a stochastic-flow network in terms of minimal paths with budget constraint," IISE Transactions, Taylor & Francis Journals, vol. 51(5), pages 547-558, May.
    14. 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.
    15. Forghani-elahabad, Majid & Kagan, Nelson & Mahdavi-Amiri, Nezam, 2019. "An MP-based approximation algorithm on reliability evaluation of multistate flow networks," Reliability Engineering and System Safety, Elsevier, vol. 191(C).
    16. 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.
    17. Yi-Kuei Lin & Cheng-Ta Yeh, 2013. "Determine the optimal carrier selection for a logistics network based on multi-commodity reliability criterion," International Journal of Systems Science, Taylor & Francis Journals, vol. 44(5), pages 949-965.
    18. Yeh, Wei-Chang, 2022. "Novel direct algorithm for computing simultaneous all-level reliability of multistate flow networks," Reliability Engineering and System Safety, Elsevier, vol. 225(C).
    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. Niu, Yi-Feng & Wang, Jun-Feng & Xu, Xiu-Zhen & Xu, Qian-Xin, 2025. "Reliability evaluation for a multi-commodity multi-state distribution network under transportation emission consideration," Reliability Engineering and System Safety, Elsevier, vol. 254(PA).
    2. 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.
    3. Niu, Yi-Feng & Zhao, Xia & Xu, Xiu-Zhen & Zhang, Shi-Yun, 2023. "Reliability assessment of a stochastic-flow distribution network with carbon emission constraint," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    4. Niu, Yi-Feng & Zhou, Run-Hui & Xu, Xiu-Zhen & Xiang, Hai-Yan, 2024. "A reliability index to measure multi-state flow network considering capacity restoration level and maintenance cost," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    5. Niu, Yi-Feng & Xiang, Hai-Yan & Xu, Xiu-Zhen, 2024. "Expected performance evaluation and optimization of a multi-distribution multi-state logistics network based on network reliability," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    6. Xu, Xiu-Zhen & Zhou, Run-Hui & Wu, Guo-Lin & Niu, Yi-Feng, 2024. "Evaluating the transmission distance-constrained reliability for a multi-state flow network," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    7. Kozyra, Paweł Marcin, 2024. "A parallel algorithm for reliability assessment of multi-state flow networks based on simultaneous finding of all multi-state minimal paths and performing state space decomposition," Reliability Engineering and System Safety, Elsevier, vol. 251(C).
    8. Huang, Ding-Hsiang, 2024. "Network reliability of a stochastic flow network by wrapping linear programming models into a Monte-Carlo simulation," Reliability Engineering and System Safety, Elsevier, vol. 252(C).
    9. Niu, Yi-Feng, 2021. "Performance measure of a multi-state flow network under reliability and maintenance cost considerations," Reliability Engineering and System Safety, Elsevier, vol. 215(C).
    10. Yeh, Wei-Chang, 2024. "A new hybrid inequality BAT for comprehensive all-level d-MP identification using minimal paths in Multistate Flow Network reliability analysis," Reliability Engineering and System Safety, Elsevier, vol. 244(C).
    11. Kozyra, Paweł Marcin, 2023. "The usefulness of (d,b)-MCs and (d,b)-MPs in network reliability evaluation under delivery or maintenance cost constraints," Reliability Engineering and System Safety, Elsevier, vol. 234(C).
    12. Yeh, Cheng-Ta & Lin, Yi-Kuei & Yeng, Louis Cheng-Lu & Huang, Pei-Tzu, 2021. "Reliability evaluation of a multistate railway transportation network from the perspective of a travel agent," Reliability Engineering and System Safety, Elsevier, vol. 214(C).
    13. Yeh, Wei-Chang & Zhu, Wenbo, 2024. "Optimal allocation of financial resources for ensuring reliable resilience in binary-state network infrastructure," Reliability Engineering and System Safety, Elsevier, vol. 250(C).
    14. Xu, Xiu-Zhen & Niu, Yi-Feng & Song, Yi-Fan, 2021. "Computing the reliability of a stochastic distribution network subject to budget constraint," Reliability Engineering and System Safety, Elsevier, vol. 216(C).
    15. 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.
    16. Chang, Ping-Chen, 2024. "A path-based simulation approach for multistate flow network reliability estimation without using boundary points," Reliability Engineering and System Safety, Elsevier, vol. 249(C).
    17. Cheng-Fu Huang & Ding-Hsiang Huang & Yi-Kuei Lin, 2022. "System reliability analysis for a cloud-based network under edge server capacity and budget constraints," Annals of Operations Research, Springer, vol. 312(1), pages 217-234, May.
    18. Yeh, Wei-Chang, 2023. "QB-II for evaluating the reliability of binary-state networks," Reliability Engineering and System Safety, Elsevier, vol. 230(C).
    19. Yeh, Wei-Chang & Hao, Zhifeng & Forghani-elahabad, Majid & Wang, Gai-Ge & Lin, Yih-Lon, 2021. "Novel Binary-Addition Tree Algorithm for Reliability Evaluation of Acyclic Multistate Information Networks," Reliability Engineering and System Safety, Elsevier, vol. 210(C).
    20. Yeh, Wei-Chang, 2020. "A new method for verifying d-MC candidates," Reliability Engineering and System Safety, Elsevier, vol. 204(C).

    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:346:y:2025:i:3:d:10.1007_s10479-025-06521-y. 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.