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

deVoil, P., Rossing, W. A. H. and Hammer, G. L. (2006) Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms. Environmental Modelling and Software, 21 9: 1368-1374. doi:10.1016/j.envsoft.2005.04.016

Author deVoil, P.
Rossing, W. A. H.
Hammer, G. L.
Title Exploring profit - Sustainability trade-offs in cropping systems using evolutionary algorithms
Journal name Environmental Modelling and Software   Check publisher's open access policy
ISSN 1364-8152
Publication date 2006-09
Sub-type Article (original research)
DOI 10.1016/j.envsoft.2005.04.016
Volume 21
Issue 9
Start page 1368
End page 1374
Total pages 7
Editor Anthony J. Jakeman
Place of publication Oxford, U.K. ; New York, U.S.A.
Publisher Elsevier Science
Collection year 2006
Language eng
Subject C1
300299 Crop and Pasture Production not elsewhere classified
230118 Optimisation
620501 Field crops
0701 Agriculture, Land and Farm Management
0703 Crop and Pasture Production
Formatted 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.
Crown Copyright © 2005.
Keyword Evolutionary algorithms
Agricultural systems modelling
Cropping system design
Computer science, interdisciplinary applications
Engineering, environmental
Environmental sciences
Q-Index Code C1

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Created: Wed, 15 Aug 2007, 08:44:39 EST