title: An interval-based regret-analysis method for identifying long-term municipal solid waste management policy under uncertainty.
abstract: In this study, an interval-based regret-analysis (IBRA) model is developed for supporting long-term planning of municipal solid waste (MSW) management activities in the City of Changchun, the capital of Jilin Province, China. The developed IBRA model incorporates approaches of interval-parameter programming (IPP) and minimax-regret (MMR) analysis within an integer programming framework, such that uncertainties expressed as both interval values and random variables can be reflected. The IBRA can account for economic consequences under all possible scenarios associated with different system costs and risk levels without making assumptions on probabilistic distributions for random variables. A regret matrix with interval elements is generated based on a matrix of interval system costs, such that desired decision alternatives can be identified according to the interval minimax regret (IMMR) criterion. The results indicate that reasonable solutions have been generated. They can help decision makers identify the desired alternatives regarding long-term MSW management with a compromise between minimized system cost and minimized system-failure risk.
authors.affiliation: S-C Energy and Environmental Research Academy, North China Electric Power University, Beijing 102206, China. bobbycuilin@163.com.cn
authors.forename: L
authors.initials: L
authors.lastname: Cui
authors.forename: L R
authors.initials: LR
authors.lastname: Chen
authors.forename: Y P
authors.initials: YP
authors.lastname: Li
authors.forename: G H
authors.initials: GH
authors.lastname: Huang
authors.forename: W
authors.initials: W
authors.lastname: Li
authors.forename: Y L
authors.initials: YL
authors.lastname: Xie
mesh_terms: D002681:China; D002947:Cities; D003659:Decision Making, Organizational; D003661:Decision Support Techniques; D011640:Public Policy; D012037:Refuse Disposal / Q000191:economics* / Q000379:methods*; D035501:Uncertainty