Development of fuzzy-approach-based optimization methodologies for supporting water supply-demand management
Date of Issue2015
School of Civil and Environmental Engineering
This research aims to develop a set of fuzzy-approach-based optimization models for water supply-demand management under uncertainty. To deal with general-shaped fuzzy parameters, a combined genetic algorithm and fuzzy simulation approach (GAFSA) was developed. The results showed that GAFSA could help analyze the balance of the overall system benefit and the failure risk. A novel superiority-inferiority-based sequential fuzzy programming (SISFP) model was also proposed. The results showed it has sought a reasonable balance among components of studied system. Further, an extended fuzzy parametric programming (EFPP) model was proposed for handling all possible fuzzy conditions. The results indicated that EFPP demonstrated a wider applicability due to its extended capacity of handling fuzzy relations in the model. Moreover, an integrated fuzzy programming and decision analysis (IFPDA) method was proposed for a multi-layer urban water distribution system management. The results indicated that, it can help analyze trade-offs between minimization of cost and reliability of system, and linking optimization model outputs with decision analysis. Finally, a robust fuzzy programming (RFP) model was proposed for a multi-reservoir system under uncertainty and climate change. The results of study case in the area of GVRD, Canada indicated that, under future condition, the water releases would increase at spring and decrease at winter under A2 emission scenario; and the dry period would extend under B2 emission scenario.
DRNTU::Engineering::Civil engineering::Water resources