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Modelling impacts of cropping systems: Demands and solutions for DEX methodology

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  • Znidarsic, Martin
  • Bohanec, Marko
  • Zupan, Blaz

Abstract

Decision modelling of diverse groups of problems makes different requirements to the modelling methodologies and software. We present an actual decision problem and the required characteristics of corresponding decision models. The problem is from agronomy and addresses the ecological and economic impacts of cropping systems, with the focus on the differences between cropping systems with conventional crops and the ones with genetically modified crops. We describe the extensions of an existing DEX qualitative multi-attribute modelling methodology, which were made to cope with the challenges of the problem. The extensions address general hierarchical structures, probabilistic utility functions and numerical values of basic attributes. A new, freely available software tool called proDEX was implemented to support the extended methodology. In this paper we describe the problem of cropping system assessment, propose methodological extensions to DEX, and present the implementation of proDEX.

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  • Znidarsic, Martin & Bohanec, Marko & Zupan, Blaz, 2008. "Modelling impacts of cropping systems: Demands and solutions for DEX methodology," European Journal of Operational Research, Elsevier, vol. 189(3), pages 594-608, September.
    • Handle: RePEc:eee:ejores:v:189:y:2008:i:3:p:594-608
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    2. Nejc Trdin & Marko Bohanec, 2018. "Extending the multi-criteria decision making method DEX with numeric attributes, value distributions and relational models," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 26(1), pages 1-41, March.
    3. Carof, M. & Colomb, B. & Aveline, A., 2013. "A guide for choosing the most appropriate method for multi-criteria assessment of agricultural systems according to decision-makers’ expectations," Agricultural Systems, Elsevier, vol. 115(C), pages 51-62.
    4. Mouron, Patrik & Heijne, Bart & Naef, Andreas & Strassemeyer, Jörn & Hayer, Frank & Avilla, Jesus & Alaphilippe, Aude & Höhn, Heinrich & Hernandez, José & Mack, Gabriele & Gaillard, Gérard & Solé, Joa, 2012. "Sustainability assessment of crop protection systems: SustainOS methodology and its application for apple orchards," Agricultural Systems, Elsevier, vol. 113(C), pages 1-15.
    5. E. Hernandez & Venkatesh Uddameri, 2010. "Selecting Agricultural Best Management Practices for Water Conservation and Quality Improvements Using Atanassov’s Intuitionistic Fuzzy Sets," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 24(15), pages 4589-4612, December.
    6. Borodin, Valeria & Bourtembourg, Jean & Hnaien, Faicel & Labadie, Nacima, 2016. "Handling uncertainty in agricultural supply chain management: A state of the art," European Journal of Operational Research, Elsevier, vol. 254(2), pages 348-359.
    7. Ivanovska, Aneta & Todorovski, Ljupčo & Debeljak, Marko & Džeroski, Sašo, 2009. "Modelling the outcrossing between genetically modified and conventional maize with equation discovery," Ecological Modelling, Elsevier, vol. 220(8), pages 1063-1072.
    8. Marjan Brelih & Uroš Rajkovič & Tomaž Ružič & Blaž Rodič & Daniel Kozelj, 2019. "Modelling decision knowledge for the evaluation of water management investment projects," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 27(3), pages 759-781, September.
    9. Johnson Holt & Adrian W. Leach & Gritta Schrader & Françoise Petter & Alan MacLeod & Dirk Jan van der Gaag & Richard H. A. Baker & John D. Mumford, 2014. "Eliciting and Combining Decision Criteria Using a Limited Palette of Utility Functions and Uncertainty Distributions: Illustrated by Application to Pest Risk Analysis," Risk Analysis, John Wiley & Sons, vol. 34(1), pages 4-16, January.

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