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Optimal Facility Location Under Random Demand With General Cost Structure

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  • V. Balachandran
  • Suresh Jain

Abstract

This paper investigates the problem of determining the optimal location of plants, and their respective production and distribution levels, in order to meet demand at a finite number of centers. The possible locations of plants are restricted to a finite set of sites, and the demands are allowed to be random. The cost structure of operating a plant is dependent on its location and is assumed to be a piecewise linear function of the production level, though not necessarily concave or convex. The paper is organized in three parts. In the first part, a branch and bound procedure for the general piecewise linear cost problem is presented, assuming that the demand is known. In the second part, a solution procedure is presented for the case when the demand is random, assuming a linear cost of production. Finally, in the third part, a solution procedure is presented for the general problem utilizing the results of the earlier parts. Certain extensions, such as capacity expansion or reduction at existing plants, and geopolitical configuration constraints can be easily incorporated within this framework.

Suggested Citation

  • V. Balachandran & Suresh Jain, 1976. "Optimal Facility Location Under Random Demand With General Cost Structure," Naval Research Logistics Quarterly, John Wiley & Sons, vol. 23(3), pages 421-436, September.
  • Handle: RePEc:wly:navlog:v:23:y:1976:i:3:p:421-436
    DOI: 10.1002/nav.3800230305
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    Cited by:

    1. Kena Zhao & Tsan Sheng Adam Ng & Xiao Liu, 2020. "A guarantee rate optimization model for wastewater treatment system design under uncertainty," Naval Research Logistics (NRL), John Wiley & Sons, vol. 67(6), pages 420-437, September.
    2. Yang, Zhongzhen & Yu, Shunan & Notteboom, Theo, 2016. "Airport location in multiple airport regions (MARs): The role of land and airside accessibility," Journal of Transport Geography, Elsevier, vol. 52(C), pages 98-110.
    3. Šárka Štádlerová & Sanjay Dominik Jena & Peter Schütz, 2023. "Using Lagrangian relaxation to locate hydrogen production facilities under uncertain demand: a case study from Norway," Computational Management Science, Springer, vol. 20(1), pages 1-32, December.
    4. Zhengguan Dai & Kathleen Xu & Melkior Ornik, 2021. "Repulsion-based p-dispersion with distance constraints in non-convex polygons," Annals of Operations Research, Springer, vol. 307(1), pages 75-91, December.

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