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The Simple Plant-Location Problem under Uncertainty

Author

Listed:
  • James V. Jucker

    (Stanford University, Stanford, California)

  • Robert C. Carlson

    (Stanford University, Stanford, California)

Abstract

There is a class of simple plant-location problems under uncertainty that can be decomposed into two simpler problems that can be solved sequentially with surprising ease. The salient characteristic of this class of problems is that for any demand generating region, one plant dominates all others as a supply source. We develop and discuss the conditions required for this dominance. The risk-averse nature of the firm is incorporated into this model with a mean-variance formulation of the objective function. The general formulation is particularized to four paradigms of firms characterized by a range of behavioral and market assumptions.

Suggested Citation

  • James V. Jucker & Robert C. Carlson, 1976. "The Simple Plant-Location Problem under Uncertainty," Operations Research, INFORMS, vol. 24(6), pages 1045-1055, December.
    • Handle: RePEc:inm:oropre:v:24:y:1976:i:6:p:1045-1055
    DOI: 10.1287/opre.24.6.1045
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    Cited by:

    1. Rosenfield, Donald B., 1996. "Global and variable cost manufacturing systems," European Journal of Operational Research, Elsevier, vol. 95(2), pages 325-343, December.
    2. Murali, Pavankumar & Ordóñez, Fernando & Dessouky, Maged M., 2012. "Facility location under demand uncertainty: Response to a large-scale bio-terror attack," Socio-Economic Planning Sciences, Elsevier, vol. 46(1), pages 78-87.
    3. Qing Ding & Lingxiu Dong & Panos Kouvelis, 2007. "On the Integration of Production and Financial Hedging Decisions in Global Markets," Operations Research, INFORMS, vol. 55(3), pages 470-489, June.
    4. Verónica Durán-Carbó & Charles ReVelle & Daniel Serra, 2006. "Spatial market expansion through mergers," Economics Working Papers 960, Department of Economics and Business, Universitat Pompeu Fabra.
    5. Jesica Armas & Angel A. Juan & Joan M. Marquès & João Pedro Pedroso, 2017. "Solving the deterministic and stochastic uncapacitated facility location problem: from a heuristic to a simheuristic," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 68(10), pages 1161-1176, October.
    6. K Sörensen, 2008. "Investigation of practical, robust and flexible decisions for facility location problems using tabu search and simulation," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 624-636, May.
    7. Current, John & Ratick, Samuel & ReVelle, Charles, 1998. "Dynamic facility location when the total number of facilities is uncertain: A decision analysis approach," European Journal of Operational Research, Elsevier, vol. 110(3), pages 597-609, November.
    8. Arostegui, Marvin Jr. & Kadipasaoglu, Sukran N. & Khumawala, Basheer M., 2006. "An empirical comparison of Tabu Search, Simulated Annealing, and Genetic Algorithms for facilities location problems," International Journal of Production Economics, Elsevier, vol. 103(2), pages 742-754, October.
    9. Taymaz, S. & Iyigun, C. & Bayindir, Z.P. & Dellaert, N.P., 2020. "A healthcare facility location problem for a multi-disease, multi-service environment under risk aversion," Socio-Economic Planning Sciences, Elsevier, vol. 71(C).
    10. Burak Kazaz & Maqbool Dada & Herbert Moskowitz, 2005. "Global Production Planning Under Exchange-Rate Uncertainty," Management Science, INFORMS, vol. 51(7), pages 1101-1119, July.
    11. Roy Cerqueti & Eleonora Cutrini, 2021. "A Framework for Modelling Economic Regional Location Processes Under Uncertainty," Journal of Quantitative Economics, Springer;The Indian Econometric Society (TIES), vol. 19(4), pages 703-725, December.
    12. Berman, Oded & Sanajian, Nima & Wang, Jiamin, 2017. "Location choice and risk attitude of a decision maker," Omega, Elsevier, vol. 66(PA), pages 170-181.

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