SMAA-based stochastic multi-criteria decision making for reservoir flood control operation

In reservoir flood control operation, candidate alternatives are generally evaluated, ranked and selected through multi-criteria decision making (MCDM) techniques, yet stochastic uncertainties both in the criteria performance values (PVs) and criteria weights (CWs) exist in the MCDM process. This paper extends the traditional MCDM methods to stochastic environments for reservoir flood control operation. The criteria PVs and CWs are treated as stochastic variables with certain probability distributions. The stochastic multicriteria acceptability analysis (SMAA) theory is introduced and the differences between conventional MCDM models and the SMAA-2 model are discussed. Methods for quantifying stochastic uncertainties in the criteria PVs are discussed and four kinds of CWs are proposed. Moreover, we define the concept of the risk of decision making errors and propose the corresponding quantitative calculation method. A three-stage MCDM procedure is recommended to guide decision makers to solve MCDM problems under stochastic environments. We apply the proposed methodology to a case study through Monte Carlo simulation to demonstrate its effectiveness and advantage. The results show that the proposed methodology can provide significant risk information for decision makers and improve the reliability of decisions for reservoir flood control operation.