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Integration of aggregate distribution and dynamic transportation planning in a supply chain with capacity disruptions and the ripple effect consideration

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  • Dmitry Ivanov
  • Richard Hartl
  • Alexandre Dolgui
  • Alexander Pavlov
  • Boris Sokolov

Abstract

We study the dynamic planning decisions of a logistics service provider that is in charge of the integrated supply chain (SC) planning. We examine an SC with multiple products, suppliers, transit nodes and customers in a multi-period mode. The logistics service provider is responsible for aggregate distribution planning and operative dynamic transportation planning. It is to decide on aggregate distribution flows as well as on the time-dependent intensities (i.e. transportation batches). These decisions are tightly incorporated but previous research considered them mostly isolated. This is quite natural since these problems contain data of different detail degree, which can be hardly incorporated in only one model. To resolve this problem, we present a hybrid multi-period, multi-commodity distribution--transportation model as an optimal control problem blended with mathematical programming. This contribution has some particular features. First, it extends previous research by elaborating on the dynamic optimal control model. Second, it considers multi-period problem statement with multiple products and alternative transportation channels. Third, we represent the integrated dynamic SC planning in order to take into account the ripple effect. With the results of this study, the dynamic issues in integrated logistics planning in the SC can be addressed, and an intelligent solution to an important problem of SC management has been proposed.

Suggested Citation

  • Dmitry Ivanov & Richard Hartl & Alexandre Dolgui & Alexander Pavlov & Boris Sokolov, 2015. "Integration of aggregate distribution and dynamic transportation planning in a supply chain with capacity disruptions and the ripple effect consideration," International Journal of Production Research, Taylor & Francis Journals, vol. 53(23), pages 6963-6979, December.
    • Handle: RePEc:taf:tprsxx:v:53:y:2015:i:23:p:6963-6979
    DOI: 10.1080/00207543.2014.986303
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    Cited by:

    1. Manzini, Massimo & Unglert, Johannes & Gyulai, Dávid & Colledani, Marcello & Jauregui-Becker, Juan Manuel & Monostori, László & Urgo, Marcello, 2018. "An integrated framework for design, management and operation of reconfigurable assembly systems," Omega, Elsevier, vol. 78(C), pages 69-84.
    2. Vimal K.E.K & Simon Peter Nadeem & Mahadharsan Ravichandran & Manavalan Ethirajan & Jayakrishna Kandasamy, 2022. "Resilience strategies to recover from the cascading ripple effect in a copper supply chain through project management," Operations Management Research, Springer, vol. 15(1), pages 440-460, June.
    3. Paul, Sanjoy Kumar & Chowdhury, Priyabrata & Moktadir, Md. Abdul & Lau, Kwok Hung, 2021. "Supply chain recovery challenges in the wake of COVID-19 pandemic," Journal of Business Research, Elsevier, vol. 136(C), pages 316-329.
    4. Ivanov, Dmitry & Dolgui, Alexandre, 2021. "OR-methods for coping with the ripple effect in supply chains during COVID-19 pandemic: Managerial insights and research implications," International Journal of Production Economics, Elsevier, vol. 232(C).
    5. Garvey, Myles D. & Carnovale, Steven, 2020. "The rippled newsvendor: A new inventory framework for modeling supply chain risk severity in the presence of risk propagation," International Journal of Production Economics, Elsevier, vol. 228(C).
    6. K. Katsaliaki & P. Galetsi & S. Kumar, 2022. "Supply chain disruptions and resilience: a major review and future research agenda," Annals of Operations Research, Springer, vol. 319(1), pages 965-1002, December.
    7. Liu, Ming & Liu, Zhongzheng & Chu, Feng & Dolgui, Alexandre & Chu, Chengbin & Zheng, Feifeng, 2022. "An optimization approach for multi-echelon supply chain viability with disruption risk minimization," Omega, Elsevier, vol. 112(C).
    8. Sinha, Priyank & Kumar, Sameer & Prakash, Surya, 2020. "Measuring and mitigating the effects of cost disturbance propagation in multi-echelon apparel supply chains," European Journal of Operational Research, Elsevier, vol. 282(1), pages 148-160.

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