Adaptive farming strategies for dynamic economic environment

Jin, Nanlin, Termansen, Mette, Hubacek, Klaus, Holden, Joseph and Kirkby, Mike (2007) Adaptive farming strategies for dynamic economic environment. In: 2007 IEEE Congress on Evolutionary Computation. IEEE, Piscataway, NJ, pp. 1213-1220. ISBN 978-1-4244-1339-3

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This paper aims to forecast the economic impacts of changing land-use in UK uplands. We assume that farmers adaptively learn and respond to a dynamic economic environment. The main research approach is the use of evolutionary algorithms for dynamic optimization. We use this approach to study how the changes of agricultural subsidy policy (CAP reform) affect farmers' land-use decisions. We compare the experimental results from our simulated evolution versus the predictions made by agricultural experts. We have found that evolutionary algorithms for dynamic optimization forecast farmers' land-use decision in line with experts' predictions. This study also shows that maintenance of the diversity of the solution set is important for evolutionary algorithms to continuously track dynamic optimums. This work provides a framework to integrate other natural, social and economic factors in future.

Item Type: Book Section
Subjects: F800 Physical and Terrestrial Geographical and Environmental Sciences
G400 Computer Science
Department: Faculties > Engineering and Environment > Computer and Information Sciences
Depositing User: Becky Skoyles
Date Deposited: 11 Aug 2014 10:56
Last Modified: 12 Oct 2019 22:29

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