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Scientific Programming
Volume 2016 (2016), Article ID 1747425, 7 pages
http://dx.doi.org/10.1155/2016/1747425
Research Article

Dependent-Chance Goal Programming for Water Resources Management under Uncertainty

1School of Science, Hebei University of Engineering, Handan 056038, China
2School of Economics and Management, Hebei University of Engineering, Handan 056038, China

Received 20 April 2016; Revised 4 July 2016; Accepted 25 July 2016

Academic Editor: Dan Ralescu

Copyright © 2016 Haiying Guo et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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.