Planning Water Resources Allocation Under Multiple Uncertainties Through a Generalized Fuzzy Two-Stage Stochastic Programming Method

被引:40
作者
Fan, Yurui [1 ]
Huang, Guohe [2 ,3 ]
Huang, Kai [1 ]
Baetz, Brian W. [4 ]
机构
[1] Univ Regina, Fac Engn, Regina, SK S4S 0A2, Canada
[2] Univ Regina, Inst Energy Environm & Sustainabil Res, UR NCEPU, Regina, SK S4S 0A2, Canada
[3] North China Elect Power Univ, Inst Energy Environm & Sustainabil Res, UR NCEPU, Beijing 102206, Peoples R China
[4] McMaster Univ, Dept Civil Engn, Hamilton, ON L8S 4L8, Canada
关键词
Decision making; dual-uncertainty; fuzzy programming; planning; water resources; QUALITY MANAGEMENT; DECISION-MAKING; MODEL; SYSTEMS;
D O I
10.1109/TFUZZ.2014.2362550
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
In this study, a generalized fuzzy two-stage stochastic programming (GFTSP) method is developed for planning water resources management systems under uncertainty. The developed GFTSP method can deal with uncertainties expressed as probability distributions, fuzzy sets, as well as fuzzy random variables. With the aid of a robust stepwise interactive algorithm, solutions for GFTSP can be generated by solving a set of deterministic submodels. Furthermore, the possibility information (expressed as fuzzy membership functions) can be reflected in the solutions for the objective function value and decision variables. The developed GFTSP approach is also applied to a water resources management and planning problem to demonstrate its applicability. Solutions of decision variables and objective function value are expressed as fuzzy membership functions, reflecting the fluctuating ranges of decision alternatives under different plausibilities. And thus, the water alternatives can be directly derived from the obtained fuzzy membership functions when the preferred a value is predefined by decision makers.
引用
收藏
页码:1488 / 1504
页数:17
相关论文
共 42 条
[1]   On solutions of fuzzy random multiobjective quadratic programming with applications in portfolio problem [J].
Ammar, E. E. .
INFORMATION SCIENCES, 2008, 178 (02) :468-484
[2]  
[Anonymous], 1995, FUZZY SET THEORY ITS
[3]  
[Anonymous], 2009, MOS-SIAM Series on Optimization
[4]   IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection [J].
Antonio Sanz, Jose ;
Fernandez, Alberto ;
Bustince, Humberto ;
Herrera, Francisco .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (03) :399-411
[5]   A fuzzy compromise approach to water resource systems planning under uncertainty [J].
Bender, MJ ;
Simonovic, SP .
FUZZY SETS AND SYSTEMS, 2000, 115 (01) :35-44
[6]   A robust risk analysis method for water resources allocation under uncertainty [J].
Chen, C. ;
Huang, G. H. ;
Li, Y. P. ;
Zhou, Y. .
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2013, 27 (03) :713-723
[7]   Fuzzy Rules Interpolation for Sparse Fuzzy Rule-Based Systems Based on Interval Type-2 Gaussian Fuzzy Sets and Genetic Algorithms [J].
Chen, Shyi-Ming ;
Chang, Yu-Chuan ;
Pan, Jeng-Shyang .
IEEE TRANSACTIONS ON FUZZY SYSTEMS, 2013, 21 (03) :412-425
[8]   Computational methods for solving fully fuzzy linear systems [J].
Dehghan, Mehdi ;
Hashemi, Behnam ;
Ghatee, Mehdi .
APPLIED MATHEMATICS AND COMPUTATION, 2006, 179 (01) :328-343
[9]   Inverse of a fuzzy matrix of fuzzy numbers [J].
Dehghan, Mehdi ;
Ghatee, Mehdi ;
Hashemi, Behnam .
INTERNATIONAL JOURNAL OF COMPUTER MATHEMATICS, 2009, 86 (08) :1433-1452
[10]   VERTEX METHOD FOR COMPUTING FUNCTIONS OF FUZZY VARIABLES [J].
DONG, WM ;
SHAH, HC .
FUZZY SETS AND SYSTEMS, 1987, 24 (01) :65-78