An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty

In this study, an interval-parameter multi-stage stochastic linear programming (IMSLP) method has been developed for water resources decision making under uncertainty. The IMSLP is a hybrid methodology of inexact optimization and multi-stage stochastic programming. It has three major advantages in c...

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Vydané v:	Advances in water resources Ročník 29; číslo 5; s. 776 - 789
Hlavní autori:	Li, Y.P., Huang, G.H., Nie, S.L.
Médium:	Journal Article
Jazyk:	English
Vydavateľské údaje:	Oxford Elsevier Ltd 01.05.2006 Elsevier Science
Predmet:	Decision making Earth sciences Earth, ocean, space Exact sciences and technology hydrologic models Hydrology Hydrology. Hydrogeology Interval optimization interval-parameter multi-stage stochastic linear programming mathematical models Multi-stage optimization Policy Scenario Stochastic stochastic processes Uncertainty water allocation water management water policy Water resources Policy Interval optimization Uncertainty Decision making Stochastic Multi-stage Water resources Scenario models probability reservoirs linear programming case studies planning water resources stochastic models optimization decision making water resource management
ISSN:	0309-1708, 1872-9657
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Abstract	In this study, an interval-parameter multi-stage stochastic linear programming (IMSLP) method has been developed for water resources decision making under uncertainty. The IMSLP is a hybrid methodology of inexact optimization and multi-stage stochastic programming. It has three major advantages in comparison to the other optimization techniques. Firstly, it extends upon the existing multi-stage stochastic programming method by allowing uncertainties expressed as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. Secondly, penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised water-allocation targets are violated. Thirdly, it cannot only handle uncertainties through constructing a set of scenarios that is representative for the universe of possible outcomes, but also reflect dynamic features of the system conditions through transactions at discrete points in time over the planning horizon. The developed IMSLP method is applied to a hypothetical case study of water resources management. The results are helpful for water resources managers in not only making decisions of water allocation but also gaining insight into the tradeoffs between environmental and economic objectives.
AbstractList	An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty is presented. It has major advantages in comparison to the other optimization techniques. It extends upon the existing multi-stage stochastic programming method by allowing uncertainties expressed as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. Penalties are exercised with resource against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised water-allocation targets are violated. The results are helpful for water resources managers in making decisions of water allocation and gaining insight into the tradeoffs between environmental and economic objectives. In this study, an interval-parameter multi-stage stochastic linear programming (IMSLP) method has been developed for water resources decision making under uncertainty. The IMSLP is a hybrid methodology of inexact optimization and multi-stage stochastic programming. It has three major advantages in comparison to the other optimization techniques. Firstly, it extends upon the existing multi-stage stochastic programming method by allowing uncertainties expressed as probability density functions and discrete intervals to be effectively incorporated within the optimization framework. Secondly, penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised water-allocation targets are violated. Thirdly, it cannot only handle uncertainties through constructing a set of scenarios that is representative for the universe of possible outcomes, but also reflect dynamic features of the system conditions through transactions at discrete points in time over the planning horizon. The developed IMSLP method is applied to a hypothetical case study of water resources management. The results are helpful for water resources managers in not only making decisions of water allocation but also gaining insight into the tradeoffs between environmental and economic objectives.
Author	Li, Y.P. Nie, S.L. Huang, G.H.
Author_xml	– sequence: 1 givenname: Y.P. surname: Li fullname: Li, Y.P. email: nlyp@env.uregina.ca organization: Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Sask., Canada S4S 0A2 – sequence: 2 givenname: G.H. surname: Huang fullname: Huang, G.H. email: gordon.huang@uregina.ca organization: Environmental Systems Engineering Program, Faculty of Engineering, University of Regina, Regina, Sask., Canada S4S 0A2 – sequence: 3 givenname: S.L. surname: Nie fullname: Nie, S.L. email: niesonglin@env.uregina.ca organization: School of Mechanical Science and Engineering, Huazhong University of Science and Technology, Wuhan, Hubei 430074, China
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Snippet	In this study, an interval-parameter multi-stage stochastic linear programming (IMSLP) method has been developed for water resources decision making under... An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty is presented. It has major advantages in...
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SubjectTerms	Decision making Earth sciences Earth, ocean, space Exact sciences and technology hydrologic models Hydrology Hydrology. Hydrogeology Interval optimization interval-parameter multi-stage stochastic linear programming mathematical models Multi-stage optimization Policy Scenario Stochastic stochastic processes Uncertainty water allocation water management water policy Water resources
Title	An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty
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