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Exact algorithms for integrated facility location and production planning problems

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  • Thomas C. Sharkey
  • Joseph Geunes
  • H. Edwin Romeijn
  • Zuo‐Jun Max Shen

Abstract

We consider a class of facility location problems with a time dimension, which requires assigning every customer to a supply facility in each of a finite number of periods. Each facility must meet all assigned customer demand in every period at a minimum cost via its production and inventory decisions. We provide exact branch‐and‐price algorithms for this class of problems and several important variants. The corresponding pricing problem takes the form of an interesting class of production planning and order selection problems. This problem class requires selecting a set of orders that maximizes profit, defined as the revenue from selected orders minus production‐planning‐related costs incurred in fulfilling the selected orders. We provide polynomial‐time dynamic programming algorithms for this class of pricing problems, as well as for generalizations thereof. Computational testing indicates the advantage of our branch‐and‐price algorithm over various approaches that use commercial software packages. These tests also highlight the significant cost savings possible from integrating location with production and inventory decisions and demonstrate that the problem is rather insensitive to forecast errors associated with the demand streams. © 2011 Wiley Periodicals, Inc. Naval Research Logistics, 2011

Suggested Citation

  • Thomas C. Sharkey & Joseph Geunes & H. Edwin Romeijn & Zuo‐Jun Max Shen, 2011. "Exact algorithms for integrated facility location and production planning problems," Naval Research Logistics (NRL), John Wiley & Sons, vol. 58(5), pages 419-436, August.
    • Handle: RePEc:wly:navres:v:58:y:2011:i:5:p:419-436
    DOI: 10.1002/nav.20458
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    Cited by:

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    2. Tönissen, D.D. & Arts, J.J., 2020. "The stochastic maintenance location routing allocation problem for rolling stock," International Journal of Production Economics, Elsevier, vol. 230(C).
    3. Wu, Tao & Huang, Le & Liang, Zhe & Zhang, Xiaoning & Zhang, Canrong, 2022. "A supervised learning-driven heuristic for solving the facility location and production planning problem," European Journal of Operational Research, Elsevier, vol. 301(2), pages 785-796.
    4. Liu, Weiwei & Kong, Nan & Wang, Mingzheng & Zhang, Lingling, 2021. "Sustainable multi-commodity capacitated facility location problem with complementarity demand functions," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 145(C).
    5. Andreea Avramescu & Richard Allmendinger & Manuel L'opez-Ib'a~nez, 2021. "Managing Manufacturing and Delivery of Personalised Medicine: Current and Future Models," Papers 2105.12699, arXiv.org.
    6. Hrabec, Dušan & Hvattum, Lars Magnus & Hoff, Arild, 2022. "The value of integrated planning for production, inventory, and routing decisions: A systematic review and meta-analysis," International Journal of Production Economics, Elsevier, vol. 248(C).
    7. Alejandro Montoya & Mario C. Vélez–Gallego & Juan G. Villegas, 2016. "Multi-product capacitated facility location problem with general production and building costs," Netnomics, Springer, vol. 17(1), pages 47-70, July.

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