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The Use of Optimization Models in Public-Sector Planning

Author

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  • E. Downey Brill, Jr.

    (University of Illinois at Urbana-Champaign)

Abstract

When applied to public-sector planning, traditional least-cost optimization models and their offspring, contemporary multiobjective models, have often been developed under the optimistic philosophy of obtaining "the answer." Frequently, such models are not very useful because there is a multitude of local optima, which result from wavy indifference functions, and because important planning elements are not captured in the formulations. Omitted elements, in fact, may imply that an optimal planning solution lies within the inferior region of a multiobjective analysis instead of along the noninferior frontier. The role of optimization methods should be re-thought in full recognition of these limitations and of the relevant planning process. They should be used to generate planning alternatives and to facilitate their evaluation and elaboration; they should also be used to provide insights and serve as catalysts for human creativity. As illustrated by recent examples, these roles may require the use of several models as well as new types of optimization formulations and modified algorithms and computer codes.

Suggested Citation

  • E. Downey Brill, Jr., 1979. "The Use of Optimization Models in Public-Sector Planning," Management Science, INFORMS, vol. 25(5), pages 413-422, May.
    • Handle: RePEc:inm:ormnsc:v:25:y:1979:i:5:p:413-422
    DOI: 10.1287/mnsc.25.5.413
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    Cited by:

    1. Maria Scaparra & Richard Church & F. Medrano, 2014. "Corridor location: the multi-gateway shortest path model," Journal of Geographical Systems, Springer, vol. 16(3), pages 287-309, July.
    2. Jing, Rui & Kuriyan, Kamal & Kong, Qingyuan & Zhang, Zhihui & Shah, Nilay & Li, Ning & Zhao, Yingru, 2019. "Exploring the impact space of different technologies using a portfolio constraint based approach for multi-objective optimization of integrated urban energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 113(C), pages 1-1.
    3. Zanakis, Stelios H. & Mandakovic, Tomislav & Gupta, Sushil K. & Sahay, Sundeep & Hong, Sungwan, 1995. "A review of program evaluation and fund allocation methods within the service and government sectors," Socio-Economic Planning Sciences, Elsevier, vol. 29(1), pages 59-79, March.
    4. Jayashankar M. Swaminathan, 2003. "Decision Support for Allocating Scarce Drugs," Interfaces, INFORMS, vol. 33(2), pages 1-11, April.
    5. Gerard Rushton, 1984. "Use of Location-Allocation Models for Improving the Geographical Accessibility of Rural Services in Developing Countries," International Regional Science Review, , vol. 9(3), pages 217-240, December.
    6. Sudhir, V. & Muraleedharan, V. R. & Srinivasan, G., 1996. "Integrated solid waste management in Urban India: A critical operational research framework," Socio-Economic Planning Sciences, Elsevier, vol. 30(3), pages 163-181, September.
    7. Wang, Szu-Hua & Huang, Shu-Li & Budd, William W., 2012. "Integrated ecosystem model for simulating land use allocation," Ecological Modelling, Elsevier, vol. 227(C), pages 46-55.
    8. Zhou, Wenchao & Gong, Peichen, 2004. "Economic effects of environmental concerns in forest management: an analysis of the cost of achieving environmental goals," Journal of Forest Economics, Elsevier, vol. 10(2), pages 97-113, September.
    9. Laura Schmitt Olabisi & Ryan Qi Wang & Arika Ligmann-Zielinska, 2015. "Why Don’t More Farmers Go Organic? Using A Stakeholder-Informed Exploratory Agent-Based Model to Represent the Dynamics of Farming Practices in the Philippines," Land, MDPI, vol. 4(4), pages 1-24, October.
    10. Oléron-Evans, Thomas P. & Salhab, Melda, 2021. "Optimal land use allocation for the Heathrow opportunity area using multi-objective linear programming," Land Use Policy, Elsevier, vol. 105(C).
    11. DeCarolis, Joseph F., 2011. "Using modeling to generate alternatives (MGA) to expand our thinking on energy futures," Energy Economics, Elsevier, vol. 33(2), pages 145-152, March.
    12. Richard L Church & Carlos A Baez, 2020. "Generating optimal and near-optimal solutions to facility location problems," Environment and Planning B, , vol. 47(6), pages 1014-1030, July.
    13. Makowski, David & Hendrix, Eligius M. T. & van Ittersum, Martin K. & Rossing, Walter A. H., 2001. "Generation and presentation of nearly optimal solutions for mixed-integer linear programming, applied to a case in farming system design," European Journal of Operational Research, Elsevier, vol. 132(2), pages 425-438, July.
    14. Cho, Huidae & Kim, Dongkyun & Olivera, Francisco & Guikema, Seth D., 2011. "Enhanced speciation in particle swarm optimization for multi-modal problems," European Journal of Operational Research, Elsevier, vol. 213(1), pages 15-23, August.

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