Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Machine Learning
Computers and Electronics in Agriculture
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In this paper a system dynamics model for organic farming development to support government decision making is presented. The system incorporates relevant variables which affect organic farming development. The user seeks answers to strategic questions related to the level of organic farming development achievable in a long term dynamic horizon. The model's basic structure is fully described and results are presented which show that the conversion process relies mainly on subsidies and self-organization resources. User can simulate different policy scenarios for organic farming and for assessing their impact on the economic and environmental parameters of organic production at aggregate level. After performing several simulation scenarios we discovered that conversion to organic farming relies on subsidies which provide the main motivation for conversion from conventional farming to organic farming. However, the subsidies are not the only driving force in the system, even more important are activities that promote organic farming, since sufficiently large subsidies could not be provided in order to complete the conversion from conventional to organic farming to the extent desired. Another important feature is food demand, determined by population size, which negatively influences the conversion to organic farming due to the increased demand leading to increased food prices.