Waste management with recourse: An inexact dynamic programming model containing fuzzy boundary intervals in objectives and constraints
The existing inexact optimization methods based on interval-parameter linear programming can hardly address problems where coefficients in objective functions are subject to dual uncertainties. In this study, a superiority–inferiority-based inexact fuzzy two-stage mixed-integer linear programming (S...
| Publicado en: | Journal of Environmental Management Vol. 91; no. 9; pp. 1898 - 1914 |
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| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Academic Press Inc.
Sep2010
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| Materias: | |
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ssf&AN=51304234&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 51304234 longDbName: Social Sciences Full Text (H.W. Wilson) uiTag: AN controlInfo: bkinfo: jinfo: jid: 03014797 EMJ jtl: Journal of Environmental Management issn: 03014797 maglogo: N pubinfo: dt: Sep2010 vid: 91 iid: 9 pid: 735 pub: Academic Press Inc. artinfo: ui: 51304234 10.1016/j.jenvman.2010.04.005 ppf: 1898 ppct: 16 formats: tig: atl: Waste management with recourse: An inexact dynamic programming model containing fuzzy boundary intervals in objectives and constraints aug: au: Tan, Q. Huang, G.H. Cai, Y.P. affil: Faculty of Engineering and Applied Science, University of Regina, Regina, Saskatchewan S4S 0A2, Canada Faculty of Engineering, Dalhousie University, Halifax, Nova Scotia B3J 1Z1, Canada su: Waste management Solid waste Industrial efficiency Dynamic programming Research methodology Mathematical models of uncertainty Linear programming Theory of constraints sug: subj: Waste management Waste collection Waste treatment and disposal Solid Waste Landfill Other Waste Collection Solid waste Industrial efficiency Dynamic programming Research methodology Mathematical models of uncertainty Linear programming Theory of constraints keyword: Fuzzy Interval Optimization Random Solid waste management Uncertainty Fuzzy Interval Optimization Random Solid waste management Uncertainty ab: The existing inexact optimization methods based on interval-parameter linear programming can hardly address problems where coefficients in objective functions are subject to dual uncertainties. In this study, a superiority–inferiority-based inexact fuzzy two-stage mixed-integer linear programming (SI-IFTMILP) model was developed for supporting municipal solid waste management under uncertainty. The developed SI-IFTMILP approach is capable of tackling dual uncertainties presented as fuzzy boundary intervals (FuBIs) in not only constraints, but also objective functions. Uncertainties expressed as a combination of intervals and random variables could also be explicitly reflected. An algorithm with high computational efficiency was provided to solve SI-IFTMILP. SI-IFTMILP was then applied to a long-term waste management case to demonstrate its applicability. Useful interval solutions were obtained. SI-IFTMILP could help generate dynamic facility-expansion and waste-allocation plans, as well as provide corrective actions when anticipated waste management plans are violated. It could also greatly reduce system-violation risk and enhance system robustness through examining two sets of penalties resulting from variations in fuzziness and randomness. Moreover, four possible alternative models were formulated to solve the same problem; solutions from them were then compared with those from SI-IFTMILP. The results indicate that SI-IFTMILP could provide more reliable solutions than the alternatives. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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