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Public Facilities Location under Elastic Demand

Author

Listed:
  • Jossef Perl

    (Bender Management Consultants Inc., Arlington, Virginia)

  • Peng-Kuan Ho

    (University of Maryland, College Park, Maryland)

Abstract

While most of the existing work on public sector location models has been developed in the context of emergency facilities, the location problem of nonemergency facilities differs in the location objective and in the elastic nature of demand. The proper location objective under elastic demand is that of maximizing Consumers' Surplus (CS). Based on a proposed framework, we formulate the CS location objective under different demand functions, representing different demand behaviors. We prove that the CS function is convex and therefore the search for optimal locations can be restricted to nodes. We present integer programming formulations of the Maximum Consumers' Surplus Location problem (MCSLP) and its generalization which includes fixed facility cost. A computational analysis compares the location behaviors under elastic and inelastic demands, and investigates the effects of demand function (demand behavior) on location behavior.

Suggested Citation

  • Jossef Perl & Peng-Kuan Ho, 1990. "Public Facilities Location under Elastic Demand," Transportation Science, INFORMS, vol. 24(2), pages 117-136, May.
    • Handle: RePEc:inm:ortrsc:v:24:y:1990:i:2:p:117-136
    DOI: 10.1287/trsc.24.2.117
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    Citations

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    Cited by:

    1. Hai Yang & S. C. Wong, 2000. "A Continuous Equilibrium Model for Estimating Market Areas of Competitive Facilities with Elastic Demand and Market Externality," Transportation Science, INFORMS, vol. 34(2), pages 216-227, May.
    2. Photis, Yorgos N. & Grekoussis, George, 2003. "Assesing demand in stochastic locational planning problems: An Artificial Intelligence approach for emergency service systems," MPRA Paper 20678, University Library of Munich, Germany.
    3. Feng Sun & Jinhe Zhang & Jingxuan Ma & Chang Wang & Senlin Hu & Dong Xu, 2021. "Evolution of the Spatial-Temporal Pattern and Social Performance Evaluation of Community Sports and Fitness Venues in Shanghai," IJERPH, MDPI, vol. 19(1), pages 1-17, December.
    4. Michael P. Johnson & Arthur P. Hurter, 2000. "Decision Support for a Housing Mobility Program Using a Multiobjective Optimization Model," Management Science, INFORMS, vol. 46(12), pages 1569-1584, December.
    5. Luís M. Fernandes & Joaquim J. Júdice & Hanif D. Sherali & António P. Antunes, 2011. "Siting and Sizing of Facilities under Probabilistic Demands," Journal of Optimization Theory and Applications, Springer, vol. 149(2), pages 420-440, May.
    6. Yorgos Photis & Yorgos Grekousis, 2006. "Spatio-Temporal Point Pattern Analysis Using Genetic Algorithms," ERSA conference papers ersa06p910, European Regional Science Association.
    7. Katja Seim & Joel Waldfogel, 2013. "Public Monopoly and Economic Efficiency: Evidence from the Pennsylvania Liquor Control Board's Entry Decisions," American Economic Review, American Economic Association, vol. 103(2), pages 831-862, April.
    8. Luís M. Fernandes & Joaquim J. Júdice & Hanif D. Sherali & António P. Antunes, 2013. "Siting and Sizing of Facilities under Probabilistic Demands," Journal of Optimization Theory and Applications, Springer, vol. 158(1), pages 284-304, July.

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