Optimization of the industrial structure facing sustainable development in resource-based city subjected to water resources under uncertainty

被引:33
作者
Gu, J. J. [1 ]
Guo, P. [2 ]
Huang, G. H. [1 ,3 ,4 ]
Shen, N. [5 ]
机构
[1] Beijing Normal Univ, Inst Ecol Simulat & Urban Ecol, Beijing 100875, Peoples R China
[2] China Agr Univ, Ctr Agr Water Res China, Beijing 100083, Peoples R China
[3] Univ Regina, Environm Syst Engn Program, Regina, SK S4S 0A2, Canada
[4] North China Elect Power Univ, Energy & Environm Res Ctr, Beijing 102206, Peoples R China
[5] Minist Environm Protect, Policy Res Ctr Environm & Econ, Beijing 10029, Peoples R China
基金
中国国家自然科学基金; 国家高技术研究发展计划(863计划);
关键词
Stochastic programming; Chance-constrained; Uncertainty; Decision making; Optimization; SOLID-WASTE MANAGEMENT; PROGRAMMING APPROACH; MODEL; FUZZY; ALLOCATION; OPTIONS; SYSTEM; BASIN;
D O I
10.1007/s00477-012-0630-9
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
An inexact stochastic fuzzy programming (ISFP) approach has been developed for the optimization of the industrial structure in resource-based city subjected to water resources under uncertainty in present study. The ISFP method incorporates the techniques of inexact stochastic programming and inexact fuzzy chance-constrained programming, where the uncertainties are expressed as interval, fuzzy sets, and probability distribution, respectively. Moreover, it can also examine the risk of violating fuzzy tolerance constraints. The developed method is subsequently employed in a realistic case for industrial development in the Jinchang city, Gansu province, China. The result can help to analyze whether the water resources carrying capacity of Jinchang can meet the need of local economic development plan under uncertainty and help decision maker to optimize the industry structure under water resource constraints to meet the maximum economic efficiency.
引用
收藏
页码:659 / 673
页数:15
相关论文
共 35 条
[1]   A finite branch-and-bound algorithm for two-stage stochastic integer programs [J].
Ahmed, S ;
Tawarmalani, M ;
Sahinidis, NV .
MATHEMATICAL PROGRAMMING, 2004, 100 (02) :355-377
[2]  
[Anonymous], 1997, Introduction to stochastic programming
[3]   A chance-constrained multi-period model for a special multi-reservoir system [J].
Azaiez, MN ;
Hariga, M ;
Al-Harkan, I .
COMPUTERS & OPERATIONS RESEARCH, 2005, 32 (05) :1337-1351
[4]   A fuzzy goal programming approach for the optimal planning of metropolitan solid waste management systems [J].
Chang, NB ;
Wang, SF .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 1997, 99 (02) :303-321
[5]   DECISION-PROBLEMS UNDER RISK AND CHANCE CONSTRAINED PROGRAMMING - DILEMMAS IN THE TRANSITION - RESPONSE [J].
CHARNES, A ;
COOPER, WW .
MANAGEMENT SCIENCE, 1983, 29 (06) :750-753
[6]   A MULTIPLICATIVE MODEL FOR EFFICIENCY ANALYSIS [J].
CHARNES, A ;
COOPER, WW ;
SEIFORD, L ;
STUTZ, J .
SOCIO-ECONOMIC PLANNING SCIENCES, 1982, 16 (05) :223-224
[7]  
ELLIS JH, 1991, APPL MATH MODEL, V15, P367
[8]   A Robust Two-Step Method for Solving Interval Linear Programming Problems within an Environmental Management Context [J].
Fan, Y. R. ;
Huang, G. H. .
JOURNAL OF ENVIRONMENTAL INFORMATICS, 2012, 19 (01) :1-9
[9]   A simple technique for the analysis of free surface flow problems [J].
France, P. W. .
ADVANCES IN WATER RESOURCES, 1981, 4 (01) :20-22
[10]   RIVER BASIN WATER-QUALITY MANAGEMENT IN STOCHASTIC ENVIRONMENT [J].
FUJIWARA, O ;
PUANGMAHA, W ;
HANAKI, K .
JOURNAL OF ENVIRONMENTAL ENGINEERING-ASCE, 1988, 114 (04) :864-877