An interval-parameter mean-CVaR two-stage stochastic programming approach for waste management under uncertainty

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• 作者：C. Dai (1)
  X. H. Cai (1)
  Y. P. Cai (2) (3)
  Q. Huo (1)
  Y. Lv (2)
  G. H. Huang (3)
  
• 关键词：Conditional value ; at ; risk ; Mean ; risk ; Interval parameter ; Uncertainty ; Solid waste management
• 刊名：Stochastic Environmental Research and Risk Assessment (SERRA)
• 出版年：2014
• 出版时间：February 2014
• 年：2014
• 卷：28
• 期：2
• 页码：167-187
• 全文大小：1,232 KB
• 作者单位：C. Dai (1)
  X. H. Cai (1)
  Y. P. Cai (2) (3)
  Q. Huo (1)
  Y. Lv (2)
  G. H. Huang (3)
  
  1. Department of Environmental Sciences, Peking University, Beijing, 100871, China
  2. State Key Laboratory of Water Environment Simulation, School of Environment, Beijing Normal University, Beijing, 100875, China
  3. Institute for Energy, Environment and Sustainable Communities, University of Regina, 120, 2 Research Drive, Regina, SK, S4S 7H9, Canada
  
• ISSN：1436-3259

文摘

In this research, approaches of interval mathematical programming, two-stage stochastic programming and conditional value-at-risk (CVaR) are incorporated within a general modeling framework, leading to an interval-parameter mean-CVaR two-stage stochastic programming (IMTSP). The developed method has several advantages: (i) it can be used to deal with uncertainties presented as interval numbers and probability distributions, (ii) its objective function simultaneously takes expected cost and system risk into consideration, thus, it is useful for helping decision makers analyze the trade-offs between cost and risk, and (iii) it can be used for supporting quantitatively evaluating the right tail of distributions of waste generation rate, which can better quantify the system risk. The IMTSP model is applied to the long-term planning of municipal solid waste management system in the City of Regina, Canada. The results indicate that IMTSP performs better in its capability of generating a series of waste management patterns under different risk-aversion levels, and also providing supports for decision makers in identifying desired waste flow strategies, considering balance between system economy and environmental quality.