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The value of integrated tactical planning optimization in the lumber supply chain

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  • Sanei Bajgiran, Omid
  • Kazemi Zanjani, Masoumeh
  • Nourelfath, Mustapha
Abstract
This study investigates the integrated annual planning of harvesting, procurement, production, distribution, and sale activities in the lumber supply chain. The problem is formulated as a mixed integer programming (MIP) model in which the binary variables correspond to the harvesting schedule over the planning horizon. The proposed model is applied on a real-size case study, which leads to a large-scale MIP model that cannot be solved by commercial solvers in a reasonable time. Consequently, we propose a heuristic algorithm which iteratively updates the search step-size of the sub-gradient method in the Lagrangian Relaxation algorithm through obtaining a new lower-bound on the objective function value based on the most recent upper-bound. While improving significantly the convergence rate, this heuristic also guarantees the feasibility of the converged solution. Furthermore, in order to measure the value of integration, we compare the integrated model with the decoupled planning models currently implemented in the lumber industry. It is observed that, depending on the number of decoupled models, 11%–84% profit improvement can be achieved by considering an integrated model. Finally, the advantage of the proposed heuristic algorithm in finding high quality plans in 51%–77% less CPU time comparing to a commercial solver and the classical Lagrangian Relaxation algorithm is demonstrated through a set of real-size test instances.

Suggested Citation

  • Sanei Bajgiran, Omid & Kazemi Zanjani, Masoumeh & Nourelfath, Mustapha, 2016. "The value of integrated tactical planning optimization in the lumber supply chain," International Journal of Production Economics, Elsevier, vol. 171(P1), pages 22-33.
    • Handle: RePEc:eee:proeco:v:171:y:2016:i:p1:p:22-33
    DOI: 10.1016/j.ijpe.2015.10.021
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    References listed on IDEAS

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    6. De Meyer, Annelies & Cattrysse, Dirk & Rasinmäki, Jussi & Van Orshoven, Jos, 2014. "Methods to optimise the design and management of biomass-for-bioenergy supply chains: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 31(C), pages 657-670.
    7. De Meyer, Annelies & Cattrysse, Dirk & Van Orshoven, Jos, 2015. "A generic mathematical model to optimise strategic and tactical decisions in biomass-based supply chains (OPTIMASS)," European Journal of Operational Research, Elsevier, vol. 245(1), pages 247-264.
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    Cited by:

    1. Pereira, Daniel Filipe & Oliveira, José Fernando & Carravilla, Maria Antónia, 2022. "Merging make-to-stock/make-to-order decisions into sales and operations planning: A multi-objective approach," Omega, Elsevier, vol. 107(C).
    2. Luo, Li & O'Hehir, Jim & Regan, Courtney M. & Meng, Li & Connor, Jeffery D. & Chow, Christopher W.K., 2021. "An integrated strategic and tactical optimization model for forest supply chain planning," Forest Policy and Economics, Elsevier, vol. 131(C).
    3. G. Rius-Sorolla & J. Maheut & S. Estellés-Miguel & J. P. Garcia-Sabater, 2020. "Coordination mechanisms with mathematical programming models for decentralized decision-making: a literature review," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 28(1), pages 61-104, March.
    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. Guarnaschelli, Armando & Bearzotti, Lorena & Montt, Cecilia, 2017. "An approach to export process management in a wood product enterprise," International Journal of Production Economics, Elsevier, vol. 190(C), pages 88-95.
    6. Omid Sanei Bajgiran & Masoumeh Kazemi Zanjani & Mustapha Nourelfath, 2017. "Forest harvesting planning under uncertainty: a cardinality-constrained approach," International Journal of Production Research, Taylor & Francis Journals, vol. 55(7), pages 1914-1929, April.
    7. Vanzetti, Nicolás & Corsano, Gabriela & Montagna, Jorge M., 2017. "A comparison between individual factories and industrial clusters location in the forest supply chain," Forest Policy and Economics, Elsevier, vol. 83(C), pages 88-98.
    8. Gregorio Rius-Sorolla & Julien Maheut & Sofia Estelles-Miguel & Jose P. Garcia-Sabater, 2021. "Collaborative Distributed Planning with Asymmetric Information. A Technological Driver for Sustainable Development," Sustainability, MDPI, vol. 13(12), pages 1-23, June.
    9. Kazemi Zanjani, Masoumeh & Sanei Bajgiran, Omid & Nourelfath, Mustapha, 2016. "A hybrid scenario cluster decomposition algorithm for supply chain tactical planning under uncertainty," European Journal of Operational Research, Elsevier, vol. 252(2), pages 466-476.

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