FSILP: Fuzzy-stochastic-interval linear programming for supporting municipal solid waste management

Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this st...

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Publicado en:Journal of Environmental Management Vol. 92; no. 4; pp. 1198 - 1210
Autores principales: Li, Pu, Chen, Bing
Formato: Case Study
Publicado: Academic Press Inc. Apr2011
Materias:
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Apr2011
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      pub: Academic Press Inc.
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        57689992
        10.1016/j.jenvman.2010.12.013
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        atl: FSILP: Fuzzy-stochastic-interval linear programming for supporting municipal solid waste management
      aug:
        au:
          Li, Pu
          Chen, Bing
        affil:
          Faculty of Engineering and Applied Science, Memorial University of Newfoundland, St. John’s, NL A1B 3X5, Canada
          Research Academy of Energy and Environmental Studies, North China Electric Power University, Beijing 102206, China
      su:
        Waste management
        Solid waste
        Industrial waste & the environment
        Fuzzy mathematics
        Linear programming
        Stochastic approximation
        Mathematical models
      sug:
        subj:
          Waste management
          Hazardous Waste Treatment and Disposal
          Administration of Air and Water Resource and Solid Waste Management Programs
          Waste treatment and disposal
          Solid Waste Landfill
          Waste collection
          Other Waste Collection
          Solid waste
          Industrial waste & the environment
          Fuzzy mathematics
          Linear programming
          Stochastic approximation
          Mathematical models
      keyword:
        Fuzzy
        Interval
        Municipal solid waste
        Optimization
        Stochastic
        Uncertainty
        Fuzzy
        Interval
        Municipal solid waste
        Optimization
        Stochastic
        Uncertainty
      ab: Although many studies on municipal solid waste management (MSW management) were conducted under uncertain conditions of fuzzy, stochastic, and interval coexistence, the solution to the conventional linear programming problems of integrating fuzzy method with the other two was inefficient. In this study, a fuzzy-stochastic-interval linear programming (FSILP) method is developed by integrating Nguyen’s method with conventional linear programming for supporting municipal solid waste management. The Nguyen’s method was used to convert the fuzzy and fuzzy-stochastic linear programming problems into the conventional linear programs, by measuring the attainment values of fuzzy numbers and/or fuzzy random variables, as well as superiority and inferiority between triangular fuzzy numbers/triangular fuzzy-stochastic variables. The developed method can effectively tackle uncertainties described in terms of probability density functions, fuzzy membership functions, and discrete intervals. Moreover, the method can also improve upon the conventional interval fuzzy programming and two-stage stochastic programming approaches, with advantageous capabilities that are easily achieved with fewer constraints and significantly reduces consumption time. The developed model was applied to a case study of municipal solid waste management system in a city. The results indicated that reasonable solutions had been generated. The solution can help quantify the relationship between the change of system cost and the uncertainties, which could support further analysis of tradeoffs between the waste management cost and the system failure risk.
      pubtype: Academic Journal
      doctype: Case Study
      src: R
    language: English
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