FLFP: A fuzzy linear fractional programming approach with double-sided fuzziness for optimal irrigation water allocation

•A fuzzy linear fractional programming (FLFP) approach with doubled-sided fuzziness is developed under uncertainty.•The model is applied to a case study for optimal irrigation water allocation in the middle reaches of Heihe River Basin.•The model addresses two objectives without considering subjecti...

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Vydáno v:Agricultural water management Ročník 199; s. 105 - 119
Hlavní autoři: Zhang, Chenglong, Guo, Ping
Médium: Journal Article
Jazyk:angličtina
Vydáno: Elsevier B.V 01.02.2018
Témata:
case studies
China
Decision-making
Double-sided fuzzy chance-constrained programming
financial economics
irrigation water
Irrigation water allocation
Linear fractional programming
Uncertainty
water allocation
watersheds
China
Decision-making
Uncertainty
Double-sided fuzzy chance-constrained programming
Irrigation water allocation
Linear fractional programming
ISSN:0378-3774, 1873-2283
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Shrnutí:•A fuzzy linear fractional programming (FLFP) approach with doubled-sided fuzziness is developed under uncertainty.•The model is applied to a case study for optimal irrigation water allocation in the middle reaches of Heihe River Basin.•The model addresses two objectives without considering subjective factors, and reflects economic water productivity.•The confidence levels of fuzzy constraints-satisfaction under both the minimum and maximum reliabilities are introduced.•The solutions facilitate analysis of tradeoffs among economic water productivity, system benefits and confidence levels. In this study, a fuzzy linear fractional programming (FLFP) approach with double-sided fuzziness is developed for optimal irrigation water allocation under uncertainty. The FLFP model can be derived from incorporating double-sided fuzzy chance-constrained programming (DFCCP) into linear fractional programming (LFP) optimization framework. The developed model can deal with uncertainty presented as fuzziness in both right-hand and left-hand sides of constraints. Moreover, it has advantages in: (1) addressing two objectives directly without considering subjective factors, (2) effectively reflecting economic water productivity between total system economic benefit and total irrigation water use, (3) introducing the concept of confidence levels of fuzzy constraints-satisfaction under both the minimum and maximum reliabilities to generate more flexible solutions and (4) facilitating in-depth analysis of interrelationships among economic water productivity, system benefits and varying confidence levels. The model is applied to a case study of irrigation water allocation in the middle reaches of Heihe River Basin, northwest China. The optimal irrigation water allocation solutions from the FLFP model can be obtained. These results can provide decision-support when deciding on selecting reasonable irrigation water resources management and agricultural production.
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content type line 23
ISSN:0378-3774
1873-2283
DOI:10.1016/j.agwat.2017.12.013