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Optimal position of supply chain delivery window: Concepts and general conditions

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  • Bushuev, Maxim A.
  • Guiffrida, Alfred L.

Abstract

The paper introduces a concept of the optimal positioning of the delivery window to the final customer in a serial supply chain. Optimally positioning the delivery window minimizes the expected penalty cost due to early and late delivery. The conditions for the optimal position of the delivery window are derived for the general form of a delivery time distribution. Closed form expressions for the optimal position of the delivery window are presented for several different forms of delivery time distributions that have been reported in the literature to model delivery performance. The optimal positioning of a delivery window is illustrated for an industrial case study.

Suggested Citation

  • Bushuev, Maxim A. & Guiffrida, Alfred L., 2012. "Optimal position of supply chain delivery window: Concepts and general conditions," International Journal of Production Economics, Elsevier, vol. 137(2), pages 226-234.
    • Handle: RePEc:eee:proeco:v:137:y:2012:i:2:p:226-234
    DOI: 10.1016/j.ijpe.2012.01.039
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    References listed on IDEAS

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    1. Ernst, Ricardo & Kamrad, Bardia & Ord, Keith, 2007. "Delivery performance in vendor selection decisions," European Journal of Operational Research, Elsevier, vol. 176(1), pages 534-541, January.
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    4. He, Xin James & Kim, Jeon G. & Hayya, Jack C., 2005. "The cost of lead-time variability: The case of the exponential distribution," International Journal of Production Economics, Elsevier, vol. 97(2), pages 130-142, August.
    5. Helena Forslund & Patrik Jonsson & Stig‐Arne Mattsson, 2009. "Order‐to‐delivery process performance in delivery scheduling environments," International Journal of Productivity and Performance Management, Emerald Group Publishing Limited, vol. 58(1), pages 41-53, January.
    6. Yeung, Wing-Kwan & Choi, Tsan-Ming & Cheng, T.C.E., 2011. "Supply chain scheduling and coordination with dual delivery modes and inventory storage cost," International Journal of Production Economics, Elsevier, vol. 132(2), pages 223-229, August.
    7. Dondo, Rodolfo & Cerda, Jaime, 2007. "A cluster-based optimization approach for the multi-depot heterogeneous fleet vehicle routing problem with time windows," European Journal of Operational Research, Elsevier, vol. 176(3), pages 1478-1507, February.
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    Cited by:

    1. Om Prakash Mishra & Vikas Kumar & Dixit Garg, 2018. "Performance evaluation of JIT enabled SCM using ANP method," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 9(2), pages 547-558, April.
    2. Chia-Nan Wang & Nhat-Luong Nhieu & Yu-Chi Chung & Huynh-Tram Pham, 2021. "Multi-Objective Optimization Models for Sustainable Perishable Intermodal Multi-Product Networks with Delivery Time Window," Mathematics, MDPI, vol. 9(4), pages 1-25, February.
    3. Hossain, Md Shahriar J. & Ohaiba, Mohamed M. & Sarker, Bhaba R., 2017. "An optimal vendor-buyer cooperative policy under generalized lead-time distribution with penalty cost for delivery lateness," International Journal of Production Economics, Elsevier, vol. 188(C), pages 50-62.
    4. Tao, Liangyan & Liu, Sifeng & Xie, Naiming & Javed, Saad Ahmed, 2021. "Optimal position of supply chain delivery window with risk-averse suppliers: A CVaR optimization approach," International Journal of Production Economics, Elsevier, vol. 232(C).
    5. Ngniatedema, Thomas & Fono, Louis Aimé & Mbondo, Georges Dieudonné, 2015. "A delayed product customization cost model with supplier delivery performance," European Journal of Operational Research, Elsevier, vol. 243(1), pages 109-119.

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