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A matheuristic for aggregate production–distribution planning with mould sharing

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  • Raa, Birger
  • Dullaert, Wout
  • Aghezzaf, El-Houssaine

Abstract

This paper discusses the aggregate production–distribution problem for a manufacturer of plastic products that are produced using injection moulding. For each product, only a single mould is available, but by exchanging moulds between plants, it is possible to produce any product at any plant. This mould sharing offers opportunities for cost savings but complicates the aggregate production–distribution planning. We present mixed integer linear programming formulations for this planning problem, and a matheuristic solution approach based on these models. The main goal of this aggregate planning tool is to quantify the opportunities that mould sharing offers to the plastics manufacturer. Computational experiments based on a real-life dataset confirm that mould sharing can reduce the production–distribution total cost with about 10%, and that the suggested matheuristic is capable of generating solutions that capture most of this significant savings potential.

Suggested Citation

  • Raa, Birger & Dullaert, Wout & Aghezzaf, El-Houssaine, 2013. "A matheuristic for aggregate production–distribution planning with mould sharing," International Journal of Production Economics, Elsevier, vol. 145(1), pages 29-37.
    • Handle: RePEc:eee:proeco:v:145:y:2013:i:1:p:29-37
    DOI: 10.1016/j.ijpe.2013.01.006
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    References listed on IDEAS

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    1. Gabriel R. Bitran & Horacio H. Yanasse, 1982. "Computational Complexity of the Capacitated Lot Size Problem," Management Science, INFORMS, vol. 28(10), pages 1174-1186, October.
    2. Gnoni, M. G. & Iavagnilio, R. & Mossa, G. & Mummolo, G. & Di Leva, A., 2003. "Production planning of a multi-site manufacturing system by hybrid modelling: A case study from the automotive industry," International Journal of Production Economics, Elsevier, vol. 85(2), pages 251-262, August.
    3. Aghezzaf, El-Houssaine, 2007. "Production planning and warehouse management in supply networks with inter-facility mold transfers," European Journal of Operational Research, Elsevier, vol. 182(3), pages 1122-1139, November.
    4. Leung, Stephen C.H. & Tsang, Sally O.S. & Ng, W.L. & Wu, Yue, 2007. "A robust optimization model for multi-site production planning problem in an uncertain environment," European Journal of Operational Research, Elsevier, vol. 181(1), pages 224-238, August.
    5. Mirzapour Al-e-hashem, S.M.J. & Malekly, H. & Aryanezhad, M.B., 2011. "A multi-objective robust optimization model for multi-product multi-site aggregate production planning in a supply chain under uncertainty," International Journal of Production Economics, Elsevier, vol. 134(1), pages 28-42, November.
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    Cited by:

    1. Sasan Khalifehzadeh & Mehdi Seifbarghy & Bahman Naderi, 2017. "Solving a fuzzy multi objective model of a production–distribution system using meta-heuristic based approaches," Journal of Intelligent Manufacturing, Springer, vol. 28(1), pages 95-109, January.
    2. 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).
    3. Guillermo Cabrera-Guerrero & Carolina Lagos & Carolina Castañeda & Franklin Johnson & Fernando Paredes & Enrique Cabrera, 2017. "Parameter Tuning for Local-Search-Based Matheuristic Methods," Complexity, Hindawi, vol. 2017, pages 1-15, December.
    4. Gansterer, Margaretha & Födermayr, Patrick & Hartl, Richard F., 2021. "The capacitated multi-level lot-sizing problem with distributed agents," International Journal of Production Economics, Elsevier, vol. 235(C).

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