A two-stage joint chance-constrained programming considering compound uncertainty of interval, random and fuzzy: a case study for agricultural water planning in an arid area

A two-stage joint chance-constrained programming is proposed based on the two-stage stochastic programming, the robust interval programming and the joint chance-constrained programming. In this study, the previous method combining interval order relations and interval possibility degrees is interpre...

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Vydáno v:Stochastic environmental research and risk assessment Ročník 36; číslo 10; s. 3281 - 3293
Hlavní autoři: Guo, Shanshan, Guo, Ping
Médium: Journal Article
Jazyk:angličtina
Vydáno: Berlin/Heidelberg Springer Berlin Heidelberg 01.10.2022
Springer Nature B.V
Témata:
Agricultural production
Agriculture
Aquatic Pollution
Arid regions
Arid zones
Case studies
Chemistry and Earth Sciences
Computational Intelligence
Computer Science
Decision making
Earth and Environmental Science
Earth Sciences
Environment
Environmental research
Linear programming
Math. Appl. in Environmental Science
Original Paper
Physics
Probability Theory and Stochastic Processes
Random variables
Risk assessment
Risk levels
Statistics for Engineering
Stochastic programming
Uncertainty
Waste Water Technology
Water demand
Water Management
Water Pollution Control
Water shortages
Water supply
Agricultural water planning
Robust programming
Two-stage stochastic programming
Joint chance-constrained programming
ISSN:1436-3240, 1436-3259
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Shrnutí:A two-stage joint chance-constrained programming is proposed based on the two-stage stochastic programming, the robust interval programming and the joint chance-constrained programming. In this study, the previous method combining interval order relations and interval possibility degrees is interpreted from the view of robust programming and then is rewritten according to the frame of robust stochastic programming and robust fuzzy programming. Based on the concept of interval possibility degree, the interval chance constrained programming is proposed and a joint chance-constrained method is generated by combining interval with the random and fuzzy chance-constrained programming. The established model is applied in agricultural water planning in an arid region. The results show that the model can provide decision makers with various planting schemes under different risk levels. According to the response of the results in different risk scenarios, decision makers can get the general impression on the influence degree of uncertainties. The analysis on the results can also show the advantage of the established model in handling multiple uncertainties and making tradeoff among different factors like the unit net benefits, penalty and water demand of crops as well as water supply. According to the comparison with the traditional two-step-method-based interval two-stage chance-constrained method, the optimality robustness and the high reference value of the established model can be proved.
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ISSN:1436-3240
1436-3259
DOI:10.1007/s00477-022-02194-2