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Optimal carrier selection based on network reliability criterion for stochastic logistics networks

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  • Lin, Yi-Kuei
  • Yeh, Cheng-Ta

Abstract

In a global economic environment, many enterprises expend their overseas markets and implement outsourcing of logistics activities to external carriers. Many enterprises pay close attention to successful delivery of their freight. Hence, how to determine the optimal carrier selection is a very critical issue for global enterprises. Generally, there are several carriers to serve on each route connecting two cities (or transfer stations) in the logistics network. Each carrier owns multiple available capacities with a probability distribution because the carrier's capacity may be partially reserved for other orders. A carrier selection means selecting exact one carrier on each route, and the logistics network according to the carrier selection is thus a stochastic logistic network. The network reliability is a performance index of freight delivery for supply chain management and is defined as the probability that d units of commodity are successfully transmitted from a supplier to a customer. This study focuses on the optimal carrier selection problem based on network reliability criterion. A GA-based algorithm that combines the minimal paths and the recursive sum of disjoint products is developed to determine the optimal carrier selection with the maximal network reliability. A practical logistics example of the LCD monitors delivery from Asia to Europe is presented to illustrate the solution procedure.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:proeco:v:128:y:2010:i:2:p:510-517
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    References listed on IDEAS

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    Citations

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    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. 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. Yi-Kuei Lin & Cheng-Fu Huang & Yi-Chieh Liao & Chih-Ching Yeh, 2017. "System reliability for a multistate intermodal logistics network with time windows," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1957-1969, April.
    4. 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.
    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. Feki, Yassin & Hajji, Adnène & Rekik, Monia, 2016. "A hedging policy for carriers’ selection under availability and demand uncertainty," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 85(C), pages 149-165.
    7. 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.
    8. Pınar Kaya Samut, 2017. "Integrated FANP-f-MIGP model for supplier selection in the renewable energy sector," Journal of Business Economics and Management, Taylor & Francis Journals, vol. 18(3), pages 427-450, May.
    9. 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.

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