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Research Article

Stochastic multi-criteria decision making framework based on SMAA-VIKOR for reservoir flood control operation

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Pages 886-901 | Received 09 Mar 2022, Accepted 31 Oct 2022, Published online: 18 Jan 2023

References

  • Aydogan, E. K. and Ozmen, M, 2017. The stochastıc vikor method and its use in reverse logistic option selection problem. RAIRO – Operations Research, 51 (2), 375–389. doi:10.1051/ro/2016027.
  • Baudry, G., Macharis, C., and Vallée, T., 2018. Range-based multi-actor multi-criteria analysis: a combined method of multi-actor multi-criteria analysis and monte carlo simulation to support participatory decision making under uncertainty. European Journal of Operational Research, 264 (1), 257–269. doi:10.1016/j.ejor.2017.06.036.
  • Bogner, K. and Pappenberger, F., 2011. Multiscale error analysis, correction, and predictive uncertainty estimation in a flood forecasting system. Water Resources Research, 47 (7). doi:10.1029/2010WR009137.
  • Chen, J., et al., 2017. A decomposition-integration risk analysis method for real-time operation of a complex flood control system. Water Resources Research, 53 (3), 2490–2506. doi:10.1002/2016WR019842.
  • Chen, J., et al., 2019. Risk analysis for real-time flood control operation of a multi-reservoir system using a dynamic bayesian network. Environmental Modelling and Software, 111, 409–420. doi:10.1016/j.envsoft.2018.10.007.
  • Chen, L., et al., 2016. Streamflow forecast uncertainty evolution and its effect on real-time reservoir operation. Journal of Hydrology, 540, 712–726. doi:10.1016/j.jhydrol.2016.06.015.
  • Diao, Y. and Wang, B., 2010. Risk analysis of flood control operation mode with forecast information based on a combination of risk sources. Science China-Technological Sciences, 53 (7SI), 1949–1956. doi:10.1007/s11431-010-3124-3.
  • Ervural, B.C., Evren, R., and Delen, D., 2018. A multi-objective decision-making approach for sustainable energy investment planning. Renewable Energy, 126, 387–402. doi:10.1016/j.renene.2018.03.051.
  • Goodarzi, L., Banihabib, M.E., and Roozbahani, A., 2019. A decision-making model for flood warning system based on ensemble forecasts. Journal of Hydrology, 573, 207–219. doi:10.1016/j.jhydrol.2019.03.040.
  • Hsu, Y., Tung, Y.-K., and Kuo, J.-T., 2011. Evaluation of dam overtopping probability induced by flood and wind. Stochastic Environmental Research and Risk Assessment, 25 (1), 35–49. doi:10.1007/s00477-010-0435-7.
  • Jaxa-Rozen, M. and Kwakkel, J., 2018. Tree-based ensemble methods for sensitivity analysis of environmental models: a performance comparison with sobol and morris techniques. Environmental Modelling and Software, 107, 245–266. doi:10.1016/j.envsoft.2018.06.011.
  • Khan, I., 2019. Power generation expansion plan and sustainability in a developing country: a multi-criteria decision analysis. Journal of Cleaner Production, 220, 707–720. doi:10.1016/j.jclepro.2019.02.161.
  • Kumar, D., et al., 2020. Sobol sensitivity analysis for risk assessment of uranium in groundwater. Environmental Geochemistry and health, 42 (6SI), 1789–1801. doi:10.1007/s10653-020-00522-5.
  • Lahdelma, R., Hokkanen, J., and Salminen, P., 1998. SMAA-stochastic multiobjective acceptability analysis. European Journal of Operational Research, 106 (1), 137–143. doi:10.1016/S0377-2217(97)00163-X.
  • Lahdelma, R. and Salminen, P., 2001. SMAA-2: stochastic multicriteria acceptability analysis for group decision making. Operations Research, 49 (3), 444–454. doi:10.1287/opre.49.3.444.11220.
  • Li, J., et al., 2019. Dynamic and intelligent modeling methods for joint operation of a flood control system. Journal of Water Resources Planning and Management, 145 (10). doi:10.1061/(ASCE)WR.1943-5452.0001110.
  • Li, M., et al., 2019. Stochastic multi-objective decision making for sustainable irrigation in a changing environment. Journal of Cleaner Production, 223, 928–945. doi:10.1016/j.jclepro.2019.03.183.
  • Liang, Z., Yang, X.W., and Yu, K.Y., 2014. Research on subjective and objective comprehensive evaluation method based on AHP and rough set. Applied Mechanics and Materials, 543-547, 1817–1821. www.scientific.net/AMM.543-547.1817.
  • Lu, H., et al., 2017. A cloud model based multi-attribute decision making approach for selection and evaluation of groundwater management schemes. Journal of Hydrology, 555, 881–893. doi:10.1016/j.jhydrol.2017.10.009.
  • Luo, J., Chen, C., and Xie, J., 2015. Multi-objective immune algorithm with preference-based selection for reservoir flood control operation. Water Resources Management, 29 (5), 1447–1466. doi:10.1007/s11269-014-0886-6.
  • Madani, K. and Lund, J.R., 2011. A monte-carlo game theoretic approach for multi-criteria decision making under uncertainty. Advances in Water Resources, 34 (5), 607–616. doi:10.1016/j.advwatres.2011.02.009.
  • Nguyen, P.V., et al., 2016. Calculating weights of social capital index using analytic hierarchy process. International Journal of Economics and Financial Issues, 6 (3), 1189–1193.
  • Opricovic, S. and Tzeng, G., 2007. Extended VIKOR method in comparison with outranking methods. European Journal of Operational Research, 178 (2), 514–529. doi:10.1016/j.ejor.2006.01.020.
  • Opricovic, S. and Tzeng, G.H., 2004. Compromise Solution by MCDM methods: a comparative analysis of VIKOR and TOPSIS. European Journal of Operational Research, 156 (2), 445–455. doi:10.1016/S0377-2217(03)00020-1.
  • Park, K., Okudan Kremer, G.E., and Ma, J., 2018. A regional information-based multi-attribute and multi-objective decision-making approach for sustainable supplier selection and order allocation. Journal of Cleaner Production, 187, 590–604. doi:10.1016/j.jclepro.2018.03.035.
  • Qin, H., et al., 2010. Multi-objective cultured differential evolution for generating optimal trade-offs in reservoir flood control operation. Water Resources Management, 24 (11), 2611–2632. doi:10.1007/s11269-009-9570-7.
  • Raei, E., et al., 2019. Multi-objective decision-making for green infrastructure planning (LID-BMPs) in urban storm water management under uncertainty. Journal of Hydrology, 579, 124091. doi:10.1016/j.jhydrol.2019.124091.
  • Sobol, I.M., 1990. Sensitivity estimates for nonlinear mathematical models. Matematicheskoe Modelirovanie, 2 (1).
  • Streimikiene, D., Šliogerienė, J., and Turskis, Z., 2016. Multi-criteria analysis of electricity generation technologies in Lithuania. Renewable Energy, 85, 148–156. doi:10.1016/j.renene.2015.06.032.
  • Tervonen, T. and Figueira, J.R., 2010. A survey on stochastic multicriteria acceptability analysis methods. Journal of Multi-Criteria Decision Analysis, 15 (1–2), 1–14. doi:10.1002/mcda.407.
  • Wang, X., et al., 2020. Multi-objective model and decision-making method for coordinating the ecological benefits of the three gorger reservoir. Journal of Cleaner Production, 270, 122066. doi:10.1016/j.jclepro.2020.122066.
  • Wolters, W.T.M. and Mareschal, B., 1995. Novel types of sensitivity analysis for additive MCDM methods. European Journal of Operational Research, 81 (2), 281–290. doi:10.1016/0377-2217(93)E0343-V.
  • Wu, H., et al., 2021. Sensitivity analysis of control parameters errors and current parameters to motion accuracy of underwater glider using Sobol’ method. Applied Ocean Research, 110. doi:10.1016/j.apor.2021.102625.
  • Wu, Y., et al., 2021. Application of marginal rate of transformation in decision making of multi-objective reservoir optimal operation scheme. Sustainability, 13 (3). doi:10.3390/su13031488.
  • Yang, Z., et al., 2022. The stochastic decision making framework for long-term multi-objective energy-water supply-ecology operation in parallel reservoirs system under uncertainties. Expert Systems with Applications, 187. doi:10.1016/j.eswa.2021.115907.
  • Zhu, F., et al., 2017. Real-time optimal flood control decision making and risk propagation under multiple uncertainties. Water Resources Research, 53 (12), 10635–10654. doi:10.1002/2017WR021480.
  • Zhu, F., et al., 2020. Stochastic multi-criteria decision making based on stepwise weight information for real-time reservoir operation. Journal of Cleaner Production, 257, 120554. doi:10.1016/j.jclepro.2020.120554.

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