Planning of municipal solid waste management systems under dual uncertainties: a hybrid interval stochastic programming approach

被引:36
作者
Cheng, G. H. [2 ]
Huang, G. H. [1 ]
Li, Y. P. [3 ]
Cao, M. F. [2 ]
Fan, Y. R. [2 ]
机构
[1] N China Elect Power Univ, Chinese Res Acad Environm Sci, Beijing 10001210220, Peoples R China
[2] N China Elect Power Univ, Energy & Environm Res Ctr, Beijing 102206, Peoples R China
[3] Peking Univ, Coll Urban & Environm Sci, Beijing 100871, Peoples R China
基金
加拿大自然科学与工程研究理事会;
关键词
Chance-constrained programming; Inexact optimization; Dual uncertainty; Random boundary interval; Solid waste management; FUZZY; GREY; MODEL;
D O I
10.1007/s00477-008-0251-5
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In this study, a random-boundary-interval linear programming (RBILP) method is developed and applied to the planning of municipal solid waste (MSW) management under dual uncertainties. In the RBILP model, uncertain inputs presented as interval numbers can be directly communicated into the optimization process; besides, intervals with uncertain lower and upper bounds can be handled through introducing the concept of random boundary interval. Consequently, robustness of the optimization process can be enhanced. To handle uncertainties with such complex presentations, an integrated chance-constrained programming and interval-parameter linear programming approach (ICCP) is proposed. ICCP can help analyze the reliability of satisfying (or risk of violating) system constraints under uncertainty. The applicability of the proposed RBILP and ICCP approach is validated through a case study of MSW management. Violations for capacity constraints are allowed under a range of significant levels. Interval solutions associated with different risk levels of constraint violation are obtained. They can be used for generating decision alternatives and thus helping waste managers to identify desired policies under various environmental, economic, and system-reliability constraints.
引用
收藏
页码:707 / 720
页数:14
相关论文
共 38 条
[1]   A chance-constrained approach to stochastic line balancing problem [J].
Agpak, Kursad ;
Gokcen, Hadi .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2007, 180 (03) :1098-1115
[2]  
[Anonymous], 1993, Continuous Univariate Distributions, DOI DOI 10.1016/0167-9473(96)90015-8
[3]   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
[4]   CHANCE-CONSTRAINED PROGRAMMING [J].
CHARNES, A ;
COOPER, WW .
MANAGEMENT SCIENCE, 1959, 6 (01) :73-79
[5]  
Charnes A., 1972, OPTIMIZING METHODS S, P391
[6]  
Chi G.F., 1998, LONG TERM PLANNING I
[7]  
ELLIS JH, 1991, APPL MATH MODEL, V15, P367
[8]   ISMISIP: an inexact stochastic mixed integer linear semi-infinite programming approach for solid waste management and planning under uncertainty [J].
Guo, P. ;
Huang, G. H. ;
He, L. .
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT, 2008, 22 (06) :759-775
[9]   Perspectives of Environmental Informatics and Systems Analysis [J].
Huang, G. H. ;
Chang, N. B. .
JOURNAL OF ENVIRONMENTAL INFORMATICS, 2003, 1 (01) :1-6
[10]  
Huang G.H., 1994, EFFECTIVE ENV MANAGE, P267