Inexact multistage stochastic integer programming for water resources management under uncertainty.
In this study, an inexact multistage stochastic integer programming (IMSIP) method is developed for water resources management under uncertainty. This method incorporates techniques of inexact optimization and multistage stochastic programming within an integer programming framework. It can deal wit...
| Publicado en: | Journal of Environmental Management Vol. 88; no. 1; pp. 93 - 108 |
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| Autores principales: | , , |
| Formato: | Artículo |
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Academic Press Inc.
July 2008
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| 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=506810347&site=ehost-live header: @attributes: shortDbName: ssf uiTerm: 506810347 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 2008 vid: 88 iid: 1 pid: 735 pub: Academic Press Inc. artinfo: ui: 506810347 10.1016/j.jenvman.2007.01.056 ppf: 93 ppct: 15 formats: tig: atl: Inexact multistage stochastic integer programming for water resources management under uncertainty. aug: au: Li, Y. P. Huang, G. H. Nie, S. L. su: Decision making Environmental management Stochastic processes Water resources development Mathematical models Uncertainty Economics sug: subj: Decision making Environmental management Stochastic processes Water resources development Mathematical models Uncertainty Economics ab: In this study, an inexact multistage stochastic integer programming (IMSIP) method is developed for water resources management under uncertainty. This method incorporates techniques of inexact optimization and multistage stochastic programming within an integer programming framework. It can deal with uncertainties expressed as both probabilities and discrete intervals, and reflect the dynamics in terms of decisions for water allocation through transactions at discrete points of a complete scenario set over a multistage context. Moreover, the IMSIP can facilitate analyses of the multiple policy scenarios that are associated with economic penalties when the promised targets are violated as well as the economies-of-scale in the costs for surplus water diversion. A case study is provided for demonstrating the applicability of the developed methodology. The results indicate that reasonable solutions have been generated for both binary and continuous variables. For all scenarios under consideration, corrective actions can be undertaken dynamically under various pre-regulated policies and can thus help minimize the penalties and costs. The IMSIP can help water resources managers to identify desired system designs against water shortage and for flood control with maximized economic benefit and minimized system-failure risk. Copyright (c) 2008 Elsevier Ltd. pubtype: Academic Journal doctype: Article src: R language: English refInfo: copyright: @attributes: flag: N holdings: @attributes: islocal: N |
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