An interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint for crop monthly water allocation
•Fuzzy-interval set is introduced into the fuzzy credibility-constrained programming.•An FIC-INMP model and corresponding solving method are developed.•The monthly water-sensitive weight is first proposed to value the monthly importance of water demand.•The model is applied to a case for crop water...
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| Veröffentlicht in: | Agricultural water management Jg. 209; S. 123 - 133 |
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| Sprache: | Englisch |
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30.10.2018
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| ISSN: | 0378-3774, 1873-2283 |
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| Abstract | •Fuzzy-interval set is introduced into the fuzzy credibility-constrained programming.•An FIC-INMP model and corresponding solving method are developed.•The monthly water-sensitive weight is first proposed to value the monthly importance of water demand.•The model is applied to a case for crop water optimal allocation and offer abundant allocation schemes under different credibility levels.
Nonlinear and conflicting objectives as well as complex uncertainties are commonly encountered by irrigation-water managers. To address such problems, an interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint (FIC-INMP) is proposed for crop water allocation. The FIC-INMP model integrating interval programming, nonlinear multiobjective programming and fuzzy-interval credibility-constrained programming could address not only the conflicts of multiple nonlinear objectives under interval uncertainty, but also the fuzziness expressed as fuzzy-interval membership function. Moreover, an interval fuzzy weighted (IFW) method is proposed to solve developed model by integrating fuzzy weighted programming approach and interval Zimmermann fuzzy method. The FIC-INMP and IFW are applied to Yingke Irrigation District to plan crop monthly water allocation and demonstrate their applicability. By fully considering the main factors in allocation, including concerns of different decision makers, normal growth of crops, local water balance and uncertainties existing in allocation, optimal crop water-allocation schemes can be obtained via the FIC-INMP and IFW. The optimal results offer abundant schemes to decision makers by trading off benefit and risk. In addition, from the comparison between single objective and multiobjective model, the multiobjective model shows better practicality due to more reasonable water allocation in critical water demand period of crops. These results can effectively contribute to the local irrigation water management and ecological restoration. |
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| AbstractList | Nonlinear and conflicting objectives as well as complex uncertainties are commonly encountered by irrigation-water managers. To address such problems, an interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint (FIC-INMP) is proposed for crop water allocation. The FIC-INMP model integrating interval programming, nonlinear multiobjective programming and fuzzy-interval credibility-constrained programming could address not only the conflicts of multiple nonlinear objectives under interval uncertainty, but also the fuzziness expressed as fuzzy-interval membership function. Moreover, an interval fuzzy weighted (IFW) method is proposed to solve developed model by integrating fuzzy weighted programming approach and interval Zimmermann fuzzy method. The FIC-INMP and IFW are applied to Yingke Irrigation District to plan crop monthly water allocation and demonstrate their applicability. By fully considering the main factors in allocation, including concerns of different decision makers, normal growth of crops, local water balance and uncertainties existing in allocation, optimal crop water-allocation schemes can be obtained via the FIC-INMP and IFW. The optimal results offer abundant schemes to decision makers by trading off benefit and risk. In addition, from the comparison between single objective and multiobjective model, the multiobjective model shows better practicality due to more reasonable water allocation in critical water demand period of crops. These results can effectively contribute to the local irrigation water management and ecological restoration. •Fuzzy-interval set is introduced into the fuzzy credibility-constrained programming.•An FIC-INMP model and corresponding solving method are developed.•The monthly water-sensitive weight is first proposed to value the monthly importance of water demand.•The model is applied to a case for crop water optimal allocation and offer abundant allocation schemes under different credibility levels. Nonlinear and conflicting objectives as well as complex uncertainties are commonly encountered by irrigation-water managers. To address such problems, an interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint (FIC-INMP) is proposed for crop water allocation. The FIC-INMP model integrating interval programming, nonlinear multiobjective programming and fuzzy-interval credibility-constrained programming could address not only the conflicts of multiple nonlinear objectives under interval uncertainty, but also the fuzziness expressed as fuzzy-interval membership function. Moreover, an interval fuzzy weighted (IFW) method is proposed to solve developed model by integrating fuzzy weighted programming approach and interval Zimmermann fuzzy method. The FIC-INMP and IFW are applied to Yingke Irrigation District to plan crop monthly water allocation and demonstrate their applicability. By fully considering the main factors in allocation, including concerns of different decision makers, normal growth of crops, local water balance and uncertainties existing in allocation, optimal crop water-allocation schemes can be obtained via the FIC-INMP and IFW. The optimal results offer abundant schemes to decision makers by trading off benefit and risk. In addition, from the comparison between single objective and multiobjective model, the multiobjective model shows better practicality due to more reasonable water allocation in critical water demand period of crops. These results can effectively contribute to the local irrigation water management and ecological restoration. |
| Author | Guo, Shanshan Wang, Youzhi Guo, Ping Yan, Zehao Zhang, Chenglong Zhang, Fan |
| Author_xml | – sequence: 1 givenname: Fan surname: Zhang fullname: Zhang, Fan organization: Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China – sequence: 2 givenname: Chenglong surname: Zhang fullname: Zhang, Chenglong organization: Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China – sequence: 3 givenname: Zehao surname: Yan fullname: Yan, Zehao organization: Department of Civil and Resource Engineering, Dalhousie University, Halifax, NS, B3H 4R2, Canada – sequence: 4 givenname: Shanshan surname: Guo fullname: Guo, Shanshan organization: Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China – sequence: 5 givenname: Youzhi surname: Wang fullname: Wang, Youzhi organization: Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China – sequence: 6 givenname: Ping surname: Guo fullname: Guo, Ping email: guop@cau.edu.cn organization: Center for Agricultural Water Research in China, China Agricultural University, Beijing, 100083, China |
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| Snippet | •Fuzzy-interval set is introduced into the fuzzy credibility-constrained programming.•An FIC-INMP model and corresponding solving method are developed.•The... Nonlinear and conflicting objectives as well as complex uncertainties are commonly encountered by irrigation-water managers. To address such problems, an... |
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| SubjectTerms | Crop water allocation crops decision making ecological restoration Fuzzy-interval credibility-constrained programming Interval nonlinear multiobjective programming irrigation management irrigation water risk Uncertainty water allocation |
| Title | An interval nonlinear multiobjective programming model with fuzzy-interval credibility constraint for crop monthly water allocation |
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