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Journal of Environmental Informatics

Online ISSN 1684-8799 / Print ISSN 1726-2135

 

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   Volume 10   Number 2   December  2007 = non-subscribed

doi:10.3808/jei.200700104 About DOIs

JEI 10(2) 2007, Pages 99-105  

© 2007 ISEIS. All rights reserved.

An Inexact Two-Stage Quadratic Program for Water Resources Planning

G. H. Huang1*, Y. P. Li1, H. N. Xiao2 and X. S. Qin1

  1. Faculty of Engineering, University of Regina, Regina, SK S4S 0A2, Canada
  2. Department of Chemical Engineering, University of New Brunswick, 15 Dineen Drive, Fredericton, NB E3B 5A3, Canada

*Corresponding author. Email: gordon.huang@uregina.ca

 

Abstract

An inexact two-stage stochastic quadratic programming (ITQP) model is developed for water resources management under uncertainty. The model is a hybrid of inexact quadratic programming and two-stage stochastic programming. It can deal with the uncertainties presented as both probabilities and intervals. Moreover, it can deal with nonlinearities in objective function to reflect the effects of marginal utility on the benefit and cost components. Using quadratic form in the objective function rather than linear one, the ITQP can minimize the unfair competition of water resources among multiple users under uncertain water conditions. In the modeling formulation, penalties are imposed when policies expressed as the promised water supply targets are violated. In its solution process, the ITQP model is transformed into two deterministic submodels based on an interactive algorithm and a derivative algorithm, which correspond to the lower and upper bounds of the desired objective. Interval solutions, which are feasible and stable in the given decision space, can then be obtained by solving the two submodels sequentially. The developed method is then applied to a case study of water resources management planning. The results indicate that reasonable solutions have been obtained. They can help provide bases for identifying desired water-allocation plans with maximized system benefit and minimized system-failure risk.


Keywords: decision making, inexact optimization, quadratic programming, two-stage stochastic, water resources

 

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Cite this paper as: G. H. Huang, Y. P. Li, H. N. Xiao and X. S. Qin, 2007. An Inexact Two-Stage Quadratic Program for Water Resources Planning. Journal of Environmental Informatics, 10(2), 99-105. http://dx.doi.org/10.3808/jei.200700104


References: 20

  1. Chen, M.J. and Huang, G.H. (2001). A derivative algorithm for inexact quadratic program-application to environmental decisionmaking under uncertainty, Eur. J. Oper. Res., 128, 570-586.
  2. Ferrero, R.W., Rivera, J.F. and Shahidehpour, S.M. (1998). A dynamic programming two-stage algorithm for long-term hydrothermal scheduling of multireservoir systems, IEEE Transactions on Power Systems, 13, 1534¨C1540.
  3. Hillier, F.S. and Lieberman, G.J. (1986) Introduction to Operations Research, fourth ed. Holden-Day, Oakland, CA.
  4. Huang, G.H., Baetz, B.W. and Patry, G.G. (1995). Gery quadratic programming and its application to municipal waste management planning under uncertainty, Eng. Optimiz., 23, 210-223.
  5. Huang, G.H. (1996). IPWM: an interval parameter water quality management model, Eng. Optimiz., 26, 79-103.
  6. Huang, G.H. and Loucks, D.P. (2000). An inexact two-stage stochastic programming model for water resources management under uncertainty, Civ. Eng. Environ. Syst., 17, 95-118.
  7. Huang, G.H. and Chang, N.B. (2003). The perspectives of environmental informatics and systems analysis, J. Environ. Inf., 1, 1-6.
  8. Kovacs, L., Boros, E. and Inotay, F. (1986). A two-stage approach for large-scale sewer systems design with application to the Lake Balaton resort area, Eur. J. Oper. Res., 23(2) 169-178.
  9. Li, Y.P., Huang, G.H. and Nie, S.L. (2006). An interval-parameter multi-stage stochastic programming model for water resources management under uncertainty, Adv. Water Resour., 29, 776-789.
  10. Li, Y.P. and Huang, G.H. (2007). Interval-parameter two-stage stochastic nonlinear programming for water resources management under uncertainty, Water Resour. Manage., Available online.
  11. Loucks, D. P., Stedinger, J.R. and Haith, D.A. (1981). Water Resource Systems Planning and Analysis, Prentice-Hall, Englewood Cliffs, N.J.
  12. Luo, B., Maqsood, I., Yin, Y.Y., Huang, G.H. and Cohen, S.J. (2003). Adaption to climate change through water trading under uncertainty - an inexact two-stage nonlinear programming approach, J. Environ. Inf., 2(2), 58-68.
  13. Maqsood, I., Huang, G.H. and Yeomans, J.S. (2005). An interval-parameter fuzzy two-stage stochastic program for water resources management under uncertainty, Eur. J. Oper. Res., 167, 208-225.
  14. Rockafellar, R.T. and Wets, R.J.B. (1986). A Lagrangian finite generation technique for solving linear-quadratic problems in stochastic programming Math, Programming Study, 28, 63-93.
  15. Ruszczynski, A. and Swietanowski, A. (1997). Accelerating the regularized decomposition method for two-stage stochastic linear problems, Eur. J. Oper. Res., 101, 328-342.
  16. Seifi, A. and Hipel, K.W. (2001). Interior-point method for reservoir operation with stochastic inflows, J. Water Resour. Plann. Manage., 127(1), 48-57.
  17. Shil'man, S.V. (1992). Stochastic quasigradient method for quadratic optimization under dependent observations, Automation and Remote Control, 53, 1881-1896.
  18. Trezos, T. and Yeh, W.W.-G. (1987). Use of stochastic dynamic programming for reservoir management, Water Resour. Res., 23, 983-996.
  19. Wang, D. and Adams, B.J. (1986). Optimization of real-time reservoir operations with Markov decision processes, Water Resour. Res., 22, 345-352.
  20. Wang, L.Z., Fang, L. and Hipel, K.W. (2003). Water resources allocation: A cooperative game theoretic approach, J. Environ. Inf., 2, 11¨C22.
  21.  



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