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An interactive inexact fuzzy bounded programming approach for agricultural water quality management

Author

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  • Zhang, Y.M.
  • Lu, H.W.
  • Nie, X.H.
  • He, L.
  • Du, P.

Abstract

An interactive inexact fuzzy bounded programming (IFBP) approach is developed through introducing the concept of fuzzy bounded intervals into an interactive fuzzy compromise programming framework. It can provide decision support for decision makers with conflicting desires of greater objective value and higher safety levels of constraints. In this model, by determining a fuzzy goal associated with different feasibility degrees from a semantic correspondence, the degrees of satisfying each objective can be calculated. Decision makers can intervene in every step of the decision process through analyzing the degrees of approaching the aspiration levels and the risks of violating the constraints. The developed method is applied to an agricultural water quality management case for optimizing planting area, manure/fertilizer application amount, and livestock husbandry size. Results indicated that an increased feasibility degree would correspond to a reduced system benefit. Generally, by analyzing risks of violating the constraints in all solution processes, decision makers who have their own aspiration levels would be able to obtain a balanced solution considering the conflict between satisfying the aspiration levels and minimizing the violation risks.

Suggested Citation

  • Zhang, Y.M. & Lu, H.W. & Nie, X.H. & He, L. & Du, P., 2014. "An interactive inexact fuzzy bounded programming approach for agricultural water quality management," Agricultural Water Management, Elsevier, vol. 133(C), pages 104-111.
    • Handle: RePEc:eee:agiwat:v:133:y:2014:i:c:p:104-111
    DOI: 10.1016/j.agwat.2013.11.003
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    References listed on IDEAS

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    Cited by:

    1. Niu, Geng & Zheng, Yi & Han, Feng & Qin, Huapeng, 2019. "The nexus of water, ecosystems and agriculture in arid areas: A multiobjective optimization study on system efficiencies," Agricultural Water Management, Elsevier, vol. 223(C), pages 1-1.
    2. Li, X.M. & Lu, H.W. & Li, J. & Du, P. & Xu, M. & He, L., 2015. "A modified fuzzy credibility constrained programming approach for agricultural water resources management—A case study in Urumqi, China," Agricultural Water Management, Elsevier, vol. 156(C), pages 79-89.
    3. Dai, C. & Cai, Y.P. & Ren, W. & Xie, Y.F. & Guo, H.C., 2016. "Identification of optimal placements of best management practices through an interval-fuzzy possibilistic programming model," Agricultural Water Management, Elsevier, vol. 165(C), pages 108-121.

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