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Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms

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DeVoil, P., Rossing, W.A.H. and Hammer, G.L. (2006) Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms. Environmental Modelling & Software, 21 (9). pp. 1368-1374.

Full text not currently attached. Access may be available via the Publisher's website or OpenAccess link.

Article Link: http://dx.doi.org/10.1016/j.envsoft.2005.04.016

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

Abstract

Models that implement the bio-physical components of agro-ecosystems are ideally suited for exploring sustainability issues in cropping systems. Sustainability may be represented as a number of objectives to be maximised or minimised. However, the full decision space of these objectives is usually very large and simplifications are necessary to safeguard computational feasibility. Different optimisation approaches have been proposed in the literature, usually based on mathematical programming techniques. Here, we present a search approach based on a multiobjective evaluation technique within an evolutionary algorithm (EA), linked to the APSIM cropping systems model.

A simple case study addressing crop choice and sowing rules in North-East Australian cropping systems is used to illustrate the methodology. Sustainability of these systems is evaluated in terms of economic performance and resource use. Due to the limited size of this sample problem, the quality of the EA optimisation can be assessed by comparison to the full problem domain. Results demonstrate that the EA procedure, parameterised with generic parameters from the literature, converges to a useable solution set within a reasonable amount of time. Frontier ‘‘peels’’ or Pareto-optimal solutions as described by the multiobjective evaluation procedure provide useful information for discussion on trade-offs between conflicting objectives.

Item Type:Article
Corporate Creators:Department of Employment, Economic Development and Innovation (DEEDI), Agri-Science, Crop and Food Science
Business groups:Crop and Food Science
Additional Information:© Elsevier.
Keywords:Evolutionary algorithms; agricultural systems modelling; cropping system design; profit; sustainability; APSIM.
Subjects:Agriculture > Agriculture (General) > Special aspects of agriculture as a whole > Sustainable agriculture
Agriculture > Agriculture (General) > Methods and systems of culture. Cropping systems
Science > Statistics > Simulation modelling
Agriculture > Agriculture (General) > Farm economics. Farm management. Agricultural mathematics
Live Archive:24 Dec 2007
Last Modified:03 Sep 2021 16:43

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