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A Practical Algorithm for Multiple-Phase Control Systems in Agricultural and Natural Resource Economics

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  • Doole, Graeme J.

Abstract

Many important problems in agricultural and natural resource economics concern an intertemporal choice between alternate dynamic systems. This significance has motivated a theoretical literature generalizing the necessary conditions of Optimal Control Theory to multiple-phase problems. However, gaining detailed insight into their practical management is difficult because general numerical solution methods are not available. This paper resolves this deficiency through the development of a flexible and efficient computational algorithm based on a set of necessary conditions derived for finite-time, multiple-phase systems. Its effectiveness is demonstrated in an application to a nontrivial crop rotation problem.

Suggested Citation

  • Doole, Graeme J., 2009. "A Practical Algorithm for Multiple-Phase Control Systems in Agricultural and Natural Resource Economics," Journal of Agricultural and Resource Economics, Western Agricultural Economics Association, vol. 34(1), April.
  • Handle: RePEc:ags:jlaare:50082
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    File URL: http://purl.umn.edu/50082
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    References listed on IDEAS

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    1. Phoebe Koundouri & Christina Christou, 2006. "Dynamic adaptation to resource scarcity and backstop availability: theory and application to groundwater ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 50(2), pages 227-245, June.
    2. Russell J. Gorddard & David J. Pannell & Greg Hertzler, 1995. "An Optimal Control Model For Integrated Weed Management Under Herbicide Resistance," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 39(1), pages 71-87, April.
    3. Makris, Miltiadis, 2001. "Necessary conditions for infinite-horizon discounted two-stage optimal control problems," Journal of Economic Dynamics and Control, Elsevier, vol. 25(12), pages 1935-1950, December.
    4. Renan U. Goetz, 1997. "Diversification in Agricultural Production: A Dynamic Model of Optimal Cropping to Manage Soil Erosion," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, vol. 79(2), pages 341-356.
    5. Graeme J. Doole, 2008. "Optimal management of annual ryegrass (Lolium rigidum Gaud.) in phase rotations in the Western Australian Wheatbelt ," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 52(3), pages 339-362, September.
    6. Kim, C. S. & Moore, Michael R. & Hanchar, John J. & Nieswiadomy, Michael, 1989. "A dynamic model of adaptation to resource depletion: theory and an application to groundwater mining," Journal of Environmental Economics and Management, Elsevier, vol. 17(1), pages 66-82, July.
    7. Graeme J. Doole & David J. Pannell, 2008. "Optimisation of a Large, Constrained Simulation Model using Compressed Annealing," Journal of Agricultural Economics, Wiley Blackwell, vol. 59(1), pages 188-206, February.
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    Cited by:

    1. MacEwan, Duncan & Howitt, Richard E., 2011. "Estimating Crop Rotations as Dynamic Cycles using Field Data," 2011 Annual Meeting, July 24-26, 2011, Pittsburgh, Pennsylvania 103635, Agricultural and Applied Economics Association.
    2. MacEwan, Duncan & Howitt, Richard E., 2011. "An Empirical Model of Crop Rotations," 2011 Conference (55th), February 8-11, 2011, Melbourne, Australia 100581, Australian Agricultural and Resource Economics Society.

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