Inexact Fuzzy-Stochastic Programming for Water Resources Management Under Multiple Uncertainties

被引:0
作者
P. Guo
G. H. Huang
Y. P. Li
机构
[1] China Agricultural University,College of Water Conservancy and Civil Engineering
[2] University of Regina,Environmental Systems Engineering Program
[3] Peking University,College of Urban and Environmental Sciences
来源
Environmental Modeling & Assessment | 2010年 / 15卷
关键词
Chance-constrained; Fuzzy; Multiple uncertainties; Two-stage; Water resources;
D O I
暂无
中图分类号
学科分类号
摘要
In this study, an interval-parameter fuzzy-stochastic two-stage programming (IFSTP) approach is developed for irrigation planning within an agriculture system under multiple uncertainties. A concept of the distribution with fuzzy-interval probability (DFIP) is defined to address multiple uncertainties expressed as integration of intervals, fuzzy sets, and probability distributions. IFSTP integrates the interval programming, two-stage stochastic programming, and fuzzy-stochastic programming within a general optimization framework. IFSTP incorporates the pre-regulated water resources management policies directly into its optimization process to analyze various policy scenarios; each scenario has different economic penalty when the promised amounts are not delivered. IFSTP is applied to an irrigation planning in a water resources management system. Solutions from IFSTP provide desired water allocation patterns, which maximize both the system’s benefits and feasibility. The results indicate that reasonable solutions are generated for objective function values and decision variables; thus, a number of decision alternatives can be generated under different levels of stream flows.
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页码:111 / 124
页数:13
相关论文
共 113 条
[1]  
Ahmed S(2004)A finite branch-and-bound algorithm for two-stage stochastic integer programs Mathematical Programming 100 355-377
[2]  
Tawarmalani M(2002)A linear programming model for cash flow management in the Brazilian construction industry Journal of Planning Literature 16 339-1908
[3]  
Sahinidis NV(2000)Parallel algorithms to solve two-stage stochastic linear programs with robustness constrains Parallel Computing 26 1889-676
[4]  
Barbosa PSF(2001)Solving nonlinear water management models using a combined genetic algorithm and linear programming approach Advances in Water Resources 24 667-352
[5]  
Pricilla RP(2007)Municipal solid waste management under uncertainty: A mixed interval parameter fuzzy-stochastic robust programming approach Environmental Engineering Science 24 338-98
[6]  
Beraldi P(2005)Sustainable water resources management under uncertainty Stochastic Environmental Research and Risk Assessment 19 97-753
[7]  
Grandinetti L(1983)Response to decision problems under risk and chance constrained programming: Dilemmas in the transitions Management Science 29 750-509
[8]  
Musmanno R(2000)Convergence properties of two-stage stochastic programming Journal of Optimization Theory and Applications 106 489-224
[9]  
Triki C(1983)Ranking fuzzy numbers in the setting of possibility theory Information Sciences 30 183-359
[10]  
Cai X(2008)Two-stage fuzzy chance-constrained programming—application to water resources management under dual uncertainties Stochastic Environmental Research and Risk Assessment 23 349-1437