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Mathematical Problems in Engineering
Volume 2013, Article ID 482095, 15 pages
http://dx.doi.org/10.1155/2013/482095
Research Article

An Inventory-Theory-Based Inexact Multistage Stochastic Programming Model for Water Resources Management

1MOE Key Laboratory of Regional Energy Systems Optimization, Sino-Canada Energy and Environmental Research Academy, North China Electric Power University, Zhuxinzhuang, Beijing 102206, China
2Faculty of Engineering and Applied Science, University of Regina, Regina, SK, Canada S4S 0A2

Received 31 December 2012; Accepted 1 March 2013

Academic Editor: Xiaosheng Qin

Copyright © 2013 M. Q. Suo 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.

Citations to this Article [4 citations]

The following is the list of published articles that have cited the current article.

  • L. Cui, Y. P. Li, G. H. Huang, and Y. Huang, “Effects of digital elevation model resolution on topography-based runoff simulation under uncertainty,” Journal Of Hydroinformatics, vol. 16, no. 6, pp. 1343–1358, 2014. View at Publisher · View at Google Scholar
  • Xiujuan Chen, Guohe Huang, Shan Zhao, Guanhui Cheng, Yinghui Wu, and Hua Zhu, “Municipal solid waste management planning for Xiamen City, China: a stochastic fractional inventory-theory-based approach,” Environmental Science and Pollution Research, 2017. View at Publisher · View at Google Scholar
  • Meiqin Suo, Pengfei Wu, and Bin Zhou, “An Integrated Method for Interval Multi-Objective Planning of a Water Resource System in the Eastern Part of Handan,” Water, vol. 9, no. 7, pp. 528, 2017. View at Publisher · View at Google Scholar
  • Hong Zhang, Minghu Ha, Hongyu Zhao, and Jianwei Song, “Inexact Multistage Stochastic Chance Constrained Programming Model for Water Resources Management under Uncertainties,” Scientific Programming, vol. 2017, pp. 1–14, 2017. View at Publisher · View at Google Scholar