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doi: 10.5281/zenodo.18267
{"references": ["Eiselt, H. and C. L. Sandblom (2010). \"Linear Programming.\" Operations Research: 13-114.", "Eiselt, H. A. and C. L. Sandblom (2007). Linear programming and its applications, Springer Verlag.", "Ganji, A., K. Ponnambalam, et al. (2006). \"A new stochastic optimization model for deficit irrigation.\" Irrigation Science 25(1): 63-73.", "Hejazi, M. I. and X. Cai (2011). \"Building more realistic reservoir optimization models using data mining \u2013 A case study of Shelbyville Reservoir.\" Advances in Water Resources 34(6): 701-717.", "Jothiprakash, V. and G. Shanthi (2008). \"Comparison of Policies Derived from Stochastic Dynamic Programming and Genetic Algorithm Models.\" Water Resources Management 23(8): 1563-1580.", "Karamouz, M., F. Szidarovszky, et al. (2003). Water resources systems analysis, Lewis Publishers.", "Kondori, E. (2008). \"Simulation; Help Managers To Make Decision.\" Journal Of Tadbir nineteenth(No. 199).", "Loucks, D. P., E. Van Beek, et al. (2005). Water resources systems planning and management: an introduction to methods, models and applications, Paris: UNESCO.", "Luenberger, D. G. and Y. Ye (2008). Linear and nonlinear programming, Springer Verlag.", "Mdazamathulla, H., F. Wu, et al. (2008). \"Comparison between genetic algorithm and linear programming approach for real time operation.\" Journal of Hydro-environment Research 2(3): 172-181.", "Mohammad Rezaiee Pajand , S. R. S. (2005). System engineering and optimization. mashhad, ferdosi.", "Needham, J. T., D. W. Watkins, et al. (2000). \"Linear programming for flood control in the Iowa and Des Moines rivers.\" Journal of Water Resources Planning and Management 126(3): 118-127.", "Novak, D. C. and C. T. Ragsdale (2003). \"A decision support methodology for stochastic multi-criteria linear programming using spreadsheets.\" Decision Support Systems 36(1): 99-116.", "Othman, F., Sadeghian, M. S., & Heydari, M. (2012). Investigate the Potential and Limitations of Meta-heuristics Algorithms Applied in Reservoir Operation Systems. 6th International Symposium on Advance Science and Technology, Kuala Lumpur , Malaysia", "Sadeghian , M. S. (2004). Guide The Operation Of Dams Reservoirs No. 272. Tehran, Ministry Of Energy, Iran Water Resources Management, Office Of Technical Standards And Criteria.", "Wurbs, R. A. (1993). \"Reservoir-system simulation and optimization models.\" Journal of Water Resources Planning and Management 119(4): 455-472.", "Yoo, J.-H. (2009). \"Maximization of hydropower generation through the application of a linear programming model.\" Journal of Hydrology 376(1-2): 182-187."]}
Operation of reservoirs is one of the most important and complicated issues in usage of dams that the designers have had challenges with for long. One of the most important solutions is choosing the best study method as well as utilizing the best engineering techniques. By using these methods and techniques, not only the operational method is studied, but also the capacity of reservoir is estimated. The most important methods in determining the capacity of reservoir are: critical period method (mass curve, sequent peak method, working table), optimization methods or system engineering techniques (linear programming, dynamic programming) and simulation method. Optimization is a method that should result in the best answer to a problem based on given purpose and limitations defined as mathematical functions. In this method, the design parameters such as the height of the dam could be estimated using mathematical models. It is also possible to evaluate the approximate operation of reservoir, based on the dam height. This paper aims at investigating the process operational studies of reservoirs. Also, it investigates the potentialities as well as the limitations of computational methods of reservoir functions in simulation and optimization methods. Finally, necessary guides in order to choose a suitable method as well as evaluating the results will be suggested.
reservoir operation; simulation; optimization;DP;LP
reservoir operation; simulation; optimization;DP;LP
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