Using composite ranking to select the most appropriate Multi-Criteria Decision Making (MCDM) method in the optimal operation of the Dam reservoir

Document Type : Research Paper

Authors

Department of Civil Engineering, Roudehen Branch, Islamic Azad University, Roudehen, Iran.

10.22055/jhs.2020.34402.1142

Abstract

In this study, the performance of the algorithms of whale, Differential evolutionary, crow search, and Gray Wolf optimization were evaluated to operate the Golestan Dam reservoir with the objective function of meeting downstream water needs. Also, after defining the objective function and its constraints, the convergence degree of the algorithms was compared with each other and with the absolute optimal values obtained from GAMS nonlinear programming method (19.41). These values together with each algorithm optimization results were ranked using six multi-criteria decision-making methods of TOPSIS, VICOR, Linmap, Codas, ELECTRE and Simple Additive Weighting after obtaining the performance evaluation criteria of each algorithm (Reliability, reversibility, and vulnerability). Finally, integration methods (Mean, Borda, and Copland techniques) were used to evaluate the performance of decision models. The results showed that the mean responses of the gray wolf, the whale, differential evolutionary, and crow search algorithms were 1.08, 1.49, 1.29 and 1.19 times the absolute optimal response and the answers’ coefficient of variation obtained by Gray Wolf algorithm was 113.2, and 1.43 times smaller than the whale, differential evolutionary, and crow search algorithms, respectively. Moreover, all integration techniques indicated the superiority of the gray wolf algorithm. Then, the Crow search, Differential evolutionary, and whale algorithms were ranked second to fourth, respectively. On the other hand, the use of these methods in solving the problem of Golestan Dam reservoir optimization was considered appropriate due to the similarity of the results obtained from the integration techniques with the results of TOPSIS, VICOR and Linmap methods.

Keywords


  1. Donyaii, A. R., Sarraf, A. P., & Ahmadi, H. (2020a). Optimization of Reservoir Dam Operation Using Gray Wolf, Crow Search and Whale Algorithms Based on the Solution of the Nonlinear Programming Model Journal of Water and Soil Science, In Press. [in Persian].
  2. Wang, Y. C., Yoshitani, J., & Fukami, K. (2005). Stochastic Multi-objective optimization of reservoirs in parallel. Hydrological Processes: An International Journal, 19(18), 3551-3567.
  3. Chang, Y. H., &Yeh, C. H. (2001). Evaluating airline competitiveness using multi-attribute decision making. Omega, 29(5), 405-415.
  4. Donyaii, A. R., Sarraf, A. P., & Ahmadi, H. (2020b). Multi-Objective Optimal Utilization Policy of Boostan Dam Reservoir Using Whale and NSGA-II Algorithms Based on Game Theory and Shannon Entropy Method, Iranian water researches Journal, In Press. [in Persian].
  5. Afkhamifar, S. & Sarraf, A. P. (2020). Prediction of groundwater level in Urmia Plain aquifer using hybrid model of wavelet Transform-Extreme Learning Machine based on quantum particle swarm optimization. Watershed Engineering and Management, 12(2): 351-364. doi: 10.22092/ijwmse.2019.126515.1669, [in Persian].
  6. Chitsaz, N., & Banihabib, M. E. (2015). Comparison of different multi criteria decision-making models in prioritizing flood management alternatives. Water Resources Management, 29(8), 2503-2525.
  7. Chitsaz, N., & Azarnivand, A. (2017). Water scarcity management in arid regions based on an extended multiple criteria technique. Water Resources Management, 31(1), 233-250.
  8. Golfam, P., Ashofteh, P. S., & Loáiciga, H. A. (2019). Evaluation of the VIKOR and FOWA Multi-Criteria Decision-Making Methods for Climate-Change Adaptation of Agricultural Water Supply. Water Resources Management, 33(8), 2867-2884.
  9. Khoshand, A., Kamalan, H. & Rezaei, H. (2018). Application of analytical hierarchy process (AHP) to assess options of energy recovery from municipal solid waste: a case study in Tehran, Iran. J Mater Cycles Waste Manag 20, 1689–1700 https://doi.org/10.1007/s10163-018-0736-3
  10. Ashrafi, S. M., & Mahmoudi, M. (2019). Developing a semi-distributed decision support system for great Karun water resources system. Journal of Applied Research in Water and Wastewater, 6(1), 16-24.
  11. Moradi, S., Akhoond-Ali, A., Radmanesh, F., & Zarei, H. (2020). Evaluation of the Effects of Geology and Agricultural Development State on the Quality of Surface Water Resources Affected by Constructing Reservoir Dams (Case Study: Marun-Jarahi Basin). Journal of Hydraulic Structures, 6(1), 20-32.
  12. Ashfteh, P. S. & Bozorghaddad, O. (2013). Extraction of reservoir operation rules under climate change conditions, Iranian Journal of Soil and Water Research, Volume 45, Number 2, pp. 113-121.
  13. Yüzgeç, U., & Eser, M. (2018). Chaotic based Differential Evolution algorithm for optimization of baker's yeast drying process. Egyptian Informatics Journal, 19(3), 151-163.
  14. Mirjalili, S., & Lewis, A. (2016). The whale optimization algorithm. Advances in engineering software, 95, 51-67.
  15. Mirjalili, S., Mirjalili, S. M., & Lewis, A. (2014). Grey wolf optimizer. Advances in engineering software, 69, 46-61.
  16. Wang, M., Chen, H., Li, H., Cai, Z., Zhao, X., Tong, C., & Xu, X. (2017). Grey wolf optimization evolving kernel extreme learning machine: Application to bankruptcy prediction. Engineering Applications of Artificial Intelligence, 63, 54-68.
  17. Askarzadeh, A. (2016). A novel metaheuristic method for solving constrained engineering optimization problems: crow search algorithm. Computers & Structures, 169, 1-12.
  18. Mohammadi, Parvin & Malekian, Arash (1396). Prioritization of watersheds in terms of flood risk based on multi-criteria decision models (theory of gray systems) (ELECTRE-TOPSIS), Echo Hydrology, Volume 4, Number 2, pp. 499-508, [in Persian].
  19. Banihabib, M. E., & Chitsaz, N. (2016). A Multi-Criteria VIKOR Model for Assessment OF Flood-Management Alternatives. Iranian of Irrigation & Water Engineering, 6 (25): 68-82[in Persian].
  20. Athawale, V. M., & Chakraborty, S. (2011). A comparative study on the ranking performance of some multi-criteria decision-making methods for industrial robot selection. International journal of industrial engineering computations, 2(4), 831-850.
  21. Lai, Y. J., & Hwang, C. L. (1992). Lecture notes in economics and mathematical systems. Fuzzy Mathematical Programming: Methods Applications.
  22. Keshavarz Ghorabaee, M., Zavadskas, E. K., Turskis, Z., & Antucheviciene, J. (2016). A New Combinative Distance-Based Assessment (CODAS) Method for Multi-Criteria Dessision-Making. Economic Computation & Economic Cybernetics Studies & Research, 50(3).
  23. Sheikh Biglou, Rana (2010). Identifying Deprived Areas of Iran Using Combined Ranking, Journal of Urban Research and Planning, Volume 2, Number 7, pp. 70-53, [in Persian].
  24. Moazami Goudarzi, F., Sarraf, A. P., & Ahmadi, H. (2020). Prediction of runoff within Maharlu basin for future 60 years using RCP scenarios. Arabian Journal of Geosciences, 13(14), 2-17.