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Speciality oils supply chain optimization: from a decoupled to an integrated planning approach

Author

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  • Guajardo, Mario

    (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)

  • Kylinger, Martin

    (Dept. of Production Economics, Linköping University)

  • Rönnqvist, Mikael

    (Dept. of Finance and Management Science, Norwegian School of Economics and Business Administration)

Abstract

We study a problem of tactical planning in a divergent supply chain. It involves decisions regarding production, inventory, internal transportation, sales and distribution to customers. The problem is motivated by the context of a company in the speciality oils industry. The overall objective at tactical level is to maximize contribution and, in order to achieve this, the planning has been divided into two separate problems. The first problem concerns sales where the nal sales and distribution planning is decentralized to individual sellers. The second problem concerns production, transportation and inventory planning through refineries, hubs and depots and is managed centrally with the aim of minimizing costs. Due to this decoupling, the solution of the two problems needs to be coordinated in order to achieve the overall objective. In the company, this is pursued through an internal price system aiming at giving the sellers the incentives needed to align their decisions with the overall objective. We propose and discuss linear programming models for the decoupled and integrated planning problems. We present numerical examples to illustrate potential effects of integration and coordination and discuss the advantages and disadvantages of the integrated over the decoupled approach. While the total contribution is higher in the integrated approach, it has also been found that the sellers' contribution can be considerably lower. Therefore, we also suggest contribution sharing rules to achieve that both the company and sellers get a better outcome under the integrated planning.

Suggested Citation

  • Guajardo, Mario & Kylinger, Martin & Rönnqvist, Mikael, 2012. "Speciality oils supply chain optimization: from a decoupled to an integrated planning approach," Discussion Papers 2012/3, Norwegian School of Economics, Department of Business and Management Science.
    • Handle: RePEc:hhs:nhhfms:2012_003
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    References listed on IDEAS

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    Cited by:

    1. Vladimir Pavlovich Klepikov & Vladimir Vladimirovich Klepikov, 2018. "Crude Oil Logistics, Production and Refining in Northern Europe," International Journal of Energy Economics and Policy, Econjournals, vol. 8(5), pages 18-28.
    2. Farahani, Mohsen & Rahmani, Donya, 2017. "Production and distribution planning in petroleum supply chains regarding the impacts of gas injection and swap," Energy, Elsevier, vol. 141(C), pages 991-1003.
    3. Emah Patrick Etokudoh & Mehraz Boolaky & Mridula Gungaphul, 2017. "Third Party Logistics Outsourcing: An Exploratory Study of the Oil and Gas Industry in Nigeria," SAGE Open, , vol. 7(4), pages 21582440177, October.
    4. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2020. "Tactical sales and operations planning: A holistic framework and a literature review of decision-making models," International Journal of Production Economics, Elsevier, vol. 228(C).
    5. Klepikov, Vladimir Pavlovich & Klepikov, Vladimir Vladimirovich, 2020. "Quantitative approach to estimating crude oil supply in Southern Europe," Resources Policy, Elsevier, vol. 69(C).
    6. Pan, Lingying & Liu, Pei & Li, Zheng, 2017. "A system dynamic analysis of China’s oil supply chain: Over-capacity and energy security issues," Applied Energy, Elsevier, vol. 188(C), pages 508-520.
    7. Moradi Nasab, N. & Amin-Naseri, M.R., 2016. "Designing an integrated model for a multi-period, multi-echelon and multi-product petroleum supply chain," Energy, Elsevier, vol. 114(C), pages 708-733.

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    More about this item

    Keywords

    Supply chain management; integrated planning; decoupled planning; linear programming; contribution sharing; OR in the oil industry;
    All these keywords.

    JEL classification:

    • C44 - Mathematical and Quantitative Methods - - Econometric and Statistical Methods: Special Topics - - - Operations Research; Statistical Decision Theory

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