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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
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From biological models to economic optimization.

Anders Ringgaard Kristensen1

  • 1HERD - Centre for Herd-oriented Education, Research and Development, Department of Large Animal Sciences, University of Copenhagen, Grønnegårdsvej 2, 1870 Frederiksberg C, Denmark.

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|December 16, 2014
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Summary

This study explores challenges in using biological models for livestock herd decision support. It discusses optimizing data collection to balance uncertainty and costs for better animal performance prediction.

Keywords:
Decision graphsDynamic programmingMarkov decision processesValue of information

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Area of Science:

  • Agricultural Science
  • Animal Science
  • Computational Biology

Background:

  • Biological models are crucial for livestock herd decision support.
  • Challenges include uncertain information, observation costs, herd dynamics, and computational methods.
  • Ensuring unbiased prediction of animal performance is a key goal.

Purpose of the Study:

  • To address challenges in applying biological models for livestock herd decision support.
  • To explore the trade-off between information uncertainty and data collection costs.
  • To discuss optimization methods for herd health management.

Main Methods:

  • Decision graphs for static decision support.
  • Markov decision processes (dynamic programming) for dynamic contexts.
  • Modeling different approaches and data collection levels to assess the value of information.

Main Results:

  • Identifying and addressing challenges in biological model application for livestock.
  • Quantifying the trade-off between uncertainty reduction and associated costs.
  • Demonstrating the utility of decision graphs and Markov decision processes.

Conclusions:

  • Optimization methods are essential for effective herd health management.
  • Balancing information value and costs improves model-based decision support.
  • Further research into computational methods can enhance livestock production.