IFRP: A hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty.
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...
| Publicado en: | Journal of Environmental Management Vol. 84; no. 1; pp. 1 - 12 |
|---|---|
| Autores principales: | , , |
| Formato: | Artículo |
| Publicado: |
Academic Press Inc.
July 2007
|
| 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=506852202&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 506852202 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: July 2007 vid: 84 iid: 1 pid: 735 pub: Academic Press Inc. artinfo: ui: 506852202 10.1016/j.jenvman.2006.04.006 ppf: 1 ppct: 11 formats: tig: atl: IFRP: A hybrid interval-parameter fuzzy robust programming approach for waste management planning under uncertainty. aug: au: Nie, X. H. Huang, G. H. Li, Y. P. su: Waste management Mathematical models Decision support systems sug: subj: Waste management Mathematical models Decision support systems ab: 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. Copyright (c) 2007 Elsevier Ltd pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
|---|