scholarly journals An Inventory-Theory-Based Inexact Multistage Stochastic Programming Model for Water Resources Management

2013 ◽  
Vol 2013 ◽  
pp. 1-15 ◽  
Author(s):  
M. Q. Suo ◽  
Y. P. Li ◽  
G. H. Huang ◽  
Y. R. Fan ◽  
Z. Li
Keyword(s):  
Water Resources ◽  
Stochastic Programming ◽  
Water Resources Management ◽  
Programming Model ◽  
Water Shortage ◽  
Multistage Stochastic Programming ◽  
Dynamic Features ◽  
Inventory Theory ◽  
Resources Management ◽  
Water Resources Systems

An inventory-theory-based inexact multistage stochastic programming (IB-IMSP) method is developed for planning water resources systems under uncertainty. The IB-IMSP is based on inexact multistage stochastic programming and inventory theory. The IB-IMSP cannot only effectively handle system uncertainties represented as probability density functions and discrete intervals but also efficiently reflect dynamic features of system conditions under different flow levels within a multistage context. Moreover, it can provide reasonable transferring schemes (i.e., the amount and batch of transferring as well as the corresponding transferring period) associated with various flow scenarios for solving water shortage problems. The applicability of the proposed IB-IMSP is demonstrated by a case study of planning water resources management. The solutions obtained are helpful for decision makers in not only identifying different transferring schemes when the promised water is not met, but also making decisions of water allocation associated with different economic objectives.

scholarly journals Inexact Multistage Stochastic Chance Constrained Programming Model for Water Resources Management under Uncertainties

2017 ◽  
Vol 2017 ◽  
pp. 1-14 ◽  
Author(s):  
Hong Zhang ◽  
Minghu Ha ◽  
Hongyu Zhao ◽  
Jianwei Song
Keyword(s):  
Water Resources ◽  
Stochastic Programming ◽  
Water Resources Management ◽  
Water Allocation ◽  
Programming Model ◽  
Management Systems ◽  
Chance Constrained Programming ◽  
Multistage Stochastic Programming ◽  
Resources Management ◽  
Constrained Programming

In order to formulate water allocation schemes under uncertainties in the water resources management systems, an inexact multistage stochastic chance constrained programming (IMSCCP) model is proposed. The model integrates stochastic chance constrained programming, multistage stochastic programming, and inexact stochastic programming within a general optimization framework to handle the uncertainties occurring in both constraints and objective. These uncertainties are expressed as probability distributions, interval with multiply distributed stochastic boundaries, dynamic features of the long-term water allocation plans, and so on. Compared with the existing inexact multistage stochastic programming, the IMSCCP can be used to assess more system risks and handle more complicated uncertainties in water resources management systems. The IMSCCP model is applied to a hypothetical case study of water resources management. In order to construct an approximate solution for the model, a hybrid algorithm, which incorporates stochastic simulation, back propagation neural network, and genetic algorithm, is proposed. The results show that the optimal value represents the maximal net system benefit achieved with a given confidence level under chance constraints, and the solutions provide optimal water allocation schemes to multiple users over a multiperiod planning horizon.

An inexact multi-objective programming model for water resources management in industrial parks of Binhai New Area, China

2015 ◽  
Vol 72 (10) ◽  
pp. 1879-1888 ◽  
Author(s):  
Y. Li ◽  
W. Li ◽  
B. Wang ◽  
X. W. Liu ◽  
Y. L. Xie ◽  
...  
Keyword(s):  
Water Resources ◽  
Water Resources Management ◽  
Programming Model ◽  
Water Shortage ◽  
Multiple Objective Programming ◽  
Multiple Objective ◽  
Resources Management ◽  
Industrial Parks ◽  
Multi Objective Programming ◽  
Objective Programming

In recent years, Binhai New Area of Tianjin has been suffering severe water shortage due to climate change and industrial activities. Integrated and effective water resources management approaches are urgent for the sustainable development of industrial parks in Binhai New Area. However, uncertainties exist in many aspects of the water resources system and are inevitably problematic for water resources planning and policy-making. To address these uncertainties, an interval multiple-objective programming model was developed here to support the long-term planning of industrial water resources management in Binhai New Area, Tianjin, China. The model incorporated both multiple-objective programming and interval linear programming into a general programming framework. The developed model could handle the uncertainties and complexities of the water management system, and also allowed decision makers to adjust fuzzy objective control decision variables to satisfy multiple holistic and interactive objectives. The solutions are useful for planning adjustments of the existing water allocation patterns in Binhai New Area.

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