dependent-chance goal programming for water resources management under uncertainty

dependent-chance goal programming for water resources management under uncertainty

;Haiying Guo;Honghua Shi;Xiaosheng Wang
environmental pollution 2016 Vol. 2016 pp. -
156
guo2016scientificdependent-chance

Abstract

Without sufficient data, consulting experts is a good way to quantify unknown parameters in water resources management which will result in human uncertainty. The aim of this paper is to introduce a new tool-uncertainty theory to deal with such uncertainty which is treated as uncertain variable with uncertainty distribution. And a dependent-chance goal programming (DCGP) model is provided for water resources management under such circumstance. In the model uncertain measure is used to measure possibility that an event will occur which is maximized by minimizing the deviation (positive or negative deviation) from target of objective event under a given priority structure. In the end, the developed model is applied to a numerical example to illustrate the effectiveness of the model. The result obtained contributes to the desired water-allocation schemes for decision-markers.

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0x95644003c57E6F55A65596E3D9Eac6813e3566dA
Article ID:
197985
Unique Identifier:
10.1155/2016/1747425
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Scimatic Chain (ID: 481)
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