Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management - Part A: Methodology.

In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stag...

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Publicado en:Journal of Environmental Management Vol. 91; no. 2; pp. 461 - 471
Autores principales: Guo, P., Huang, G. H.
Formato: Artículo
Publicado: Academic Press Inc. November/December 2009
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: November/December 2009
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      pub: Academic Press Inc.
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        506946403
        10.1016/j.jenvman.2009.09.014
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        atl: Inexact fuzzy-stochastic mixed-integer programming approach for long-term planning of waste management - Part A: Methodology.
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        au:
          Guo, P.
          Huang, G. H.
      su:
        Decision support systems
        Waste management
        Environmental policy
        Canada
      sug:
        subj:
          Canada
          Decision support systems
          Waste management
          Environmental policy
      ab: In this study, an inexact fuzzy chance-constrained two-stage mixed-integer linear programming (IFCTIP) approach is proposed for supporting long-term planning of waste-management systems under multiple uncertainties in the City of Regina, Canada. The method improves upon the existing inexact two-stage programming and mixed-integer linear programming techniques by incorporating uncertainties expressed as multiple uncertainties of intervals and dual probability distributions within a general optimization framework. The developed method can provide an effective linkage between the predefined environmental policies and the associated economic implications. Four special characteristics of the proposed method make it unique compared with other optimization techniques that deal with uncertainties. Firstly, it provides a linkage to predefined policies that have to be respected when a modeling effort is undertaken; secondly, it is useful for tackling uncertainties presented as intervals, probabilities, fuzzy sets and their incorporation; thirdly, it facilitates dynamic analysis for decisions of facility-expansion planning and waste-flow allocation within a multi-facility, multi-period, multi-level, and multi-option context; fourthly, the penalties are exercised with recourse against any infeasibility, which permits in-depth analyses of various policy scenarios that are associated with different levels of economic consequences when the promised solid waste-generation rates are violated. In a companion paper, the developed method is applied to a real case for the long-term planning of waste management in the City of Regina, Canada. Copyright (c) 2009 Elsevier Ltd.
      pubtype: Academic Journal
      doctype: Article
      src: R
    language: English
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