Optimum Water Resources Allocation Planning at Basin Scale by Integrating MODSIM and Cuckoo Optimization Algorithm

Document Type : Original Article

Authors

1 M.Sc. Graduate, Department of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran

2 Assistant Professor, Department of Civil, Water and Environmental Engineering, Shahid Beheshti University, Tehran, Iran.

Abstract

In today's world, increasing water needs because of increasing in human population and the advancement of industry and agriculture is inevitable. On the one hand the restrictions and the principle of sustainability in the management of water resources, water supply and all the existing requirements made it impossible. To understand systematic approaching and integrated management of water resources allocation need to know the rules of programming. This method can estimate how to achieve the goals of water resources management. According to the characteristics of different methods used in water resources planning topics, can be concluded that the effective optimization of process issues of water resources management at basin level requires the combination use of a comprehensive simulation model with capability of fixing details at the basin scale and an optimization algorithm with capability of having many decision variables, and appropriate speed to the convergence response of optimization problem and also the lack of need to change the current relationships and equations on the question form. The factors enumerated show the necessity of doing this research, in this regard, the optimum utilization of the water system's tank with the optimum allocation on the basin with the combination of MODSIM model as a simulation model and COA (Cuckoo Optimization Algorithm) as an optimum algorithm, were reviewed. Feature of MODSIM model in direct contact with the COA algorithm can be outlined for this remarkable method.

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Main Subjects

References

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Iran-Water Resources Research
Volume 13, Issue 4
January 2018
Pages 1-16

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History

  • Receive Date: 17 November 2016
  • Revise Date: 05 May 2017
  • Accept Date: 12 May 2017

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