title: IFRP: a hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty.
abstract: In this study, an interval-parameter fuzzy-robust programming (IFRP) model is developed and applied to the planning of solid waste management systems under uncertainty. As an extension of the existing fuzzy-robust programming and interval-parameter linear programming methods, the IFRP can explicitly address system uncertainties with complex presentations. Parameters in the IFRP model can be represented as interval numbers and/or fuzzy membership functions, such that the uncertainties can be directly communicated into the optimization process and resulting solution. Furthermore, highly uncertain information for the lower and upper bounds of interval parameters that exist due to the complexity of the real world can be effectively handled through introducing the concept of fuzzy boundary interval. Consequently, robustness of the optimization process and solution can be enhanced. Results of the case study indicate that useful solutions for planning municipal solid waste management practices can be generated. They reflect a compromise between optimality and stability of the study system. Willingness to pay higher costs will guarantee the system stability; however, a desire to reduce the costs will run the risk of potential instability of the system. The results also suggest that the proposed hybrid methodology is applicable to practical problems that are associated with highly complex and uncertain information.
authors.affiliation: Sino-Canada Center of Energy and Environmental Research, North China Electric Power University, Beijing, China 102206.
authors.forename: X H
authors.initials: XH
authors.lastname: Nie
authors.forename: G H
authors.initials: GH
authors.lastname: Huang
authors.forename: Y P
authors.initials: YP
authors.lastname: Li
authors.forename: L
authors.initials: L
authors.lastname: Liu
mesh_terms: D000465:Algorithms; D004777:Environment; D005544:Forecasting; D017143:Fuzzy Logic; D008962:Models, Theoretical; D012037:Refuse Disposal / Q000379:methods*; D018570:Risk Assessment; D012984:Software; D018505:Waste Management / Q000379:methods*