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Principles of Dynamic Optimization in Resource Management

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  • John O.S. Kennedy

Abstract

The type of resource problem amenable to static analysis is distinguished from that requiring dynamic analysis. Possibly due to the apparent complexity of optimal control theory methods, often dynamic models have not been applied where they would be appropriate. In this article dynamic programming arguments are used to derive optimality conditions directly and simply. They are derived for a renewable resource such as a fishery, but they have application to resource management in general. The approach is illustrated by examples to the extraction of a depletable resource, to feeding for weight gain, and to applying fertilizer when some fertilizer carriers over from one crop season to another. Conditions for the optimal replacement of biological units are also considered.

Suggested Citation

  • John O.S. Kennedy, 1988. "Principles of Dynamic Optimization in Resource Management," Agricultural Economics, International Association of Agricultural Economists, vol. 2(1), pages 57-72, June.
    • Handle: RePEc:bla:agecon:v:2:y:1988:i:1:p:57-72
    DOI: 10.1111/j.1574-0862.1988.tb00038.x
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    1. Khairo, Salahadin A. & Norton, Mark R. & Garden, P. & Graham, Phil & Langford, Colin & Armstrong, P. & Brassil, T., 2009. "The impact of superphosphate and surface-applied lime on the profitability and sustainability of wool production on the tablelands of NSW," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47939, Australian Agricultural and Resource Economics Society.
    2. Fisher, Brian S. & Thorpe, Sally, 1990. "Issues In Resource Management," Australian Journal of Agricultural Economics, Australian Agricultural and Resource Economics Society, vol. 34(2), pages 1-16, August.
    3. Mullen, John D. & Helyar, K.R. & Pagan, Phil, 2000. "Economic and Biological Perspectives on Off-site Effects Associated with Soil Acidification," 2000 Conference (44th), January 23-25, 2000, Sydney, Australia 123709, Australian Agricultural and Resource Economics Society.
    4. Bernd Lengers & Wolfgang Britz, 2012. "The choice of emission indicators in environmental policy design: an analysis of GHG abatement in different dairy farms based on a bio-economic model approach," Review of Agricultural and Environmental Studies - Revue d'Etudes en Agriculture et Environnement, INRA Department of Economics, vol. 93(2), pages 117-144.
    5. Jones, Randall E. & Cacho, Oscar J., 2000. "A Dynamic Optimisation Model of Weed Control," 2000 Conference (44th), January 23-25, 2000, Sydney, Australia 123685, Australian Agricultural and Resource Economics Society.
    6. Farquharson, Robert J. & Cacho, Oscar J. & Mullen, John D., 2005. "An economic approach to soil fertility management for wheat production in New South Wales and Queensland," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137866, Australian Agricultural and Resource Economics Society.
    7. Aluwihare, Parakrama B. & Jones, Randall E. & Letcher, Rebecca A., 2005. "The farm level impacts of water sharing plans in the Namoi Valley: A stochastic dynamic programming analysis," 2005 Conference (49th), February 9-11, 2005, Coff's Harbour, Australia 137742, Australian Agricultural and Resource Economics Society.
    8. Zull, Andrew F. & Cacho, Oscar J. & Lawes, Roger A., 2009. "Optimising woody-weed control," 2009 Conference (53rd), February 11-13, 2009, Cairns, Australia 47620, Australian Agricultural and Resource Economics Society.
    9. Jean-Pierre Corriou, 2021. "Dynamic Optimization," Springer Optimization and Its Applications, in: Numerical Methods and Optimization, chapter 0, pages 653-708, Springer.
    10. Mullen, John D., 2001. "An Economic Persective On Land Degradation Issues," Research Reports 27999, New South Wales Department of Primary Industries Research Economists.

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