Journal of Innovative Research in Engineering Sciences



Water resources management and optimization of flood design using the moth-flame metaheuristics algorithm

Ali sheykhi Garousi, Farinaz zamani

Using linear, nonlinear, and dynamic planning methods for water resources management has been common since a long time ago, but owing to some deficiencies, today much attention is paid to heuristics methods. Among the optimization algorithms, the moth-fire algorithm can be considered. In this paper, the optimization of the flood management plan was carried out using the moth-fire algorithm. In order to consider the flood damage in each month, the estimated damage values are determined according to the floods routing with different return periods in the downstream of the dam using MATLAB software. The sum of the expected damage of flood and lack of need supply in the objective function will be minimized using the moth-fire algorithm. The results of a case study carried out on the Aras dam indicate the efficiency of the proposed optimization model in supplying the needs and reducing the flood damage in the downstream.

Published on the web: 2019-03-09
Received : 2019-02-12
Submitting : 2019-01-16
Keyword:1- Flood
Keyword:2- Optimization
Keyword:3- Dam
Keyword:4- MATLAB Software
Keyword:5- Moth-fire algorithm

File Article

Download pdf download article


1. Waghwala, R. K., & Agnihotri, P. G. (2019). Flood risk assessment and resilience strategies for flood risk management: A case study of Surat City. International Journal of Disaster Risk Reduction, 101155.[Scholar]

2. Morss, R. E., Wilhelmi, O. V., Downton, M. W., & Gruntfest, E. (2005). Flood risk, uncertainty, and scientific information for decision making: lessons from an interdisciplinary project. Bulletin of the American Meteorological Society86(11), 1593-1602. [Scholar]

3. Alves, A., Gersonius, B., Kapelan, Z., Vojinovic, Z., & Sanchez, A. (2019). Assessing the Co-Benefits of green-blue-grey infrastructure for sustainable urban flood risk management. Journal of environmental management239, 244-254. [Scholar]

4. Roos, M. M., Hartmann, T. T., Spit, T. T., & Johann, G. G. (2017). Constructing risks–Internalisation of flood risks in the flood risk management plan. Environmental science & policy74, 23-29. [Scholar]

5. Chang, F. J., Chen, L., & Chang, L. C. (2005). Optimizing the reservoir operating rule curves by genetic algorithms. Hydrological Processes: An International Journal19(11), 2277-2289. [Scholar]

6. East, V. (1994). Water resources system optimization using genetic algorithms. In Hydroinformatics' 94, Proc., 1st Int. Conf. on Hydroinformatics, Balkema, Rotterdam, the Netherlands. [Scholar]

7. Hasebe, M., & Nagayama, Y. (2002). Reservoir operation using the neural network and fuzzy systems for dam control and operation support. Advances in Engineering Software33(5), 245-260. [Scholar]

8. Karamouz, M., Araghinejad, S., & Haghnegahdar, A. (2004). Calibration and Validation of Long-Term Streamflow Forecasting Models. In Critical Transitions in Water and Environmental Resources Management (pp. 1-9). [Scholar]

9. Deb, K., Agrawal, S., Pratap, A., & Meyarivan, T. (2000, September). A fast elitist non-dominated sorting genetic algorithm for multi-objective optimization: NSGA-II. In International conference on parallel problem solving from nature (pp. 849-858). Springer, Berlin, Heidelberg. [Scholar]

10. Badrzadeh, H., Sarukkalige, R., & Jayawardena, A. W. (2015). Hourly runoff forecasting for flood risk management: Application of various computational intelligence models. Journal of Hydrology529, 1633-1643. [Scholar]

11. Mirjalili, S. (2015). Moth-flame optimization algorithm: A novel nature-inspired heuristic paradigm. Knowledge-Based Systems89, 228-249. [Scholar]

12. Alimoradi, S., Faraj, R., & Torabian, A. (2018). Effects of residual aluminum on hybrid membrane bioreactor (Coagulation-MBR) performance, treating dairy wastewater. Chemical Engineering and Processing - Process Intensification, 133, 320-324. [Scholar]

13. Alimoradi, S., Hable, R., Stagg-Williams, S., & Sturm, B. (2017a). Fate of phosphorous after thermochemical treatment of algal biomass. Proceedings of the Water Environment Federation, 2017(8), 3888-3891. [Scholar]

14. Sina Lotfollahi, M Ghorji, TV HOSEINI (2019), The effect of non-simultaneous excavation of closely-spaced twin tunnels on ground surface settlement, Journal of Civil Engineering and Materials Application, 3, 138-145. [Scholar]