A Hybrid Stochastic-Interval Analytic Hierarchy Process Approach for Prioritizing the Strategies of Reusing Treated Wastewater

Abstract

This paper proposes a hybrid stochastic-interval analytic hierarchy process (SIAHP) approach to address uncertainty in group decision making by integrating interval judgment, probabilistic distribution, lexicographic goal programming, and Monte Carlo simulation. A case study related to wastewater treatment plant (WWTP) effluent reuse was conducted to demonstrate the feasibility of the proposed approach. Four candidate alternatives including city moat landscaping, municipal reuse, industrial reuse, and agricultural irrigation were evaluated by five experts according to technical, economic, and environmental criteria. The results suggest that industrial reuse (0.18–0.3) is more preferred over municipal reuse (0.16–0.25) or agricultural irrigation (0.17–0.26) in most replications. The final score of city moat landscaping ranges from 0.11 to 0.31 which indicates a great divergence of expert opinions. It can be concluded that choosing industrial reuse seems to give the best overall account of technical, economic, and environmental concerns. The proposed SIAHP approach can aid group decision making by accommodating linguistic information and dealing with insufficient information or biased opinions.