Inexact Minimax Regret Integer Programming for Long-Term Planning of Municipal Solid Waste Management - Part A: Methodology Development

被引:8
|
作者
Li, Yongping [1 ]
Huang, Gordon H. [2 ,3 ]
机构
[1] Peking Univ, Coll Urban & Environm Sci, Beijing 100871, Peoples R China
[2] Univ Regina, Fac Engn, Environm Syst Engn Program, Regina, SK S4S 0A2, Canada
[3] Beijing Normal Univ, Chinese Res Acad Environm Sci, Beijing 10001210087, Peoples R China
关键词
decision making; environment; inexact optimization; minimax regret; mixed integer linear programming; solid waste; uncertainty; ENVIRONMENTAL-MANAGEMENT; MODEL DEVELOPMENT; UNCERTAINTY; SYSTEMS;
D O I
10.1089/ees.2007.0241.ptA
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In real-world municipal solid waste (MSW) management systems, identification of proper policies under uncertainty for accomplishing desired waste-disposal targets is critical. An inexact minimax regret integer programming (IMMRIP) method for the long-term planning of MSW management is developed. It incorporates the technique of minimax regret analysis (MMR) into an interval-parameter mixed-integer linear programming (IMILP) framework. The IMMRIP method can handle dual uncertainties presented as both random variables and interval values; it only needs a list of scenarios without any assumption on their probability distributions. It can facilitate dynamic analysis for decisions of system-capacity expansion and/or development within a multi-facility and multi-period context. Moreover, it can also be used for analyzing multiple scenarios associated with different system costs and risk levels. An interval-element cost matrix can be transformed into an interval-element regret matrix based on an interactive algorithm. Solutions based on an inexact minimax regret criterion can identify desired alternatives for MSW management and planning under a variety of uncertainties. In a companion paper, the developed method will be applied to a real case study in the City of Regina, Canada.
引用
收藏
页码:209 / 218
页数:10
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