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Optimal management of agricultural systems

Mayer, D.G. and Rossing, W.A.H. and de Devoil, P. and Groot, J.C. and McPhee, M.J. and Oltjen, J.W. (2008) Optimal management of agricultural systems. In: Success in Evolutionary Computation. Studies in Computational Intelligence, 92 . Springer Berlin / Heidelberg, pp. 141-163.

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Article Link(s): http://dx.doi.org/10.1007/978-3-540-76286-7_7

Publisher URL: http://www.springerlink.com

Abstract

To remain competitive, many agricultural systems are now being run along business lines. Systems methodologies are being incorporated, and here evolutionary computation is a valuable tool for identifying more profitable or sustainable solutions. However, agricultural models typically pose some of the more challenging problems for optimisation. This chapter outlines these problems, and then presents a series of three case studies demonstrating how they can be overcome in practice. Firstly, increasingly complex models of Australian livestock enterprises show that evolutionary computation is the only viable optimisation method for these large and difficult problems. On-going research is taking a notably efficient and robust variant, differential evolution, out into real-world systems. Next, models of cropping systems in Australia demonstrate the challenge of dealing with competing objectives, namely maximising farm profit whilst minimising resource degradation. Pareto methods are used to illustrate this trade-off, and these results have proved to be most useful for farm managers in this industry. Finally, land-use planning in the Netherlands demonstrates the size and spatial complexity of real-world problems. Here, GIS-based optimisation techniques are integrated with Pareto methods, producing better solutions which were acceptable to the competing organizations. These three studies all show that evolutionary computation remains the only feasible method for the optimisation of large, complex agricultural problems. An extra benefit is that the resultant population of candidate solutions illustrates trade-offs, and this leads to more informed discussions and better education of the industry decision-makers.

Item Type:Book Section
Business groups:Agri-Science, Crop and Food Science, Animal Science
Additional Information:© Springer-Verlag Berlin Heidelberg.
Keywords:Agricultural models; systems methodologies; agricultural systems; Pareto methods; cropping systems; land use planning; optimisation techniques.
Subjects:Agriculture > Agriculture (General) > Methods and systems of culture. Cropping systems
Science > Mathematics > Computer software
Deposited On:02 Feb 2009 04:06
Last Modified:25 Oct 2011 06:00

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