Soft Computing in Water Resources Management by Using OWA Operator

The Ordered Weighted Averaging (OWA) operator is an efficient multi criteria decision making (MCDM) method. This study introduces a new method to obtain the order weights of this operator. The new method is based on the combination of fuzzy quantifiers and neat OWA operators. Fuzzy quantifiers are applied for soft computing in modeling the social preferences (optimism degree of the decision maker, DM). In using neat operators, the ordering of the inputs is not needed resulting in better computation efficiency.

One of the frequently-used ways to control water shortages is inter-basin water transfer (IBWT). Efficient decision making on this subject is however a real challenge for the water institutions. These decisions should include multiple criteria, model uncertainty, and also the optimistic/pessimistic view of the decision makers. The theoretical results are illustrated by ranking four IBWT projects for the Zayanderud basin, Iran. The results demonstrate that by using the new method, more sensitive decisions can be obtained to deal with limited water resources.

The results of this study also show that this new method is more appropriate than the other traditional MCDM methods in systems engineering since it takes the optimism/pessimism nature of the DM into account in a quantifiable way. The comparison of the computational results with the current state of the projects shows the optimistic character of the DM. A sensitivity analysis illustrates how the rankings of the water projects depend on the optimism degree of the DMs.