For a multireservoir system, where the number of reservoirs islarge, the conventional modelling by classical stochastic dynamicprogramming (SDP) presents difficulty, due to the curse ofdimensionality inherent in the model solution. It takes a longtime to obtain a steady state policy and also it requires largeamount of computer storage space, which form drawbacks inapplication. An attempt is made to explore the concept of fuzzysets to provide a viable alternative in this context. Theapplication of fuzzy set theory to water resources systems isillustrated through the formulation of a fuzzy mathematicalprogramming model to a multireservoir system with a number ofupstream parallel reservoirs, and one downstream reservoir. Thestudy is aimed to minimize the sum of deviations of the irrigationwithdrawals from their target demands, on a monthly basis, over ayear. Uncertainty in reservoir inflows is considered by treatingthem as fuzzy sets. The model considers deterministic irrigationdemands. The model is applied to a three reservoir system in theUpper Cauvery River basin, South India. The model clearlydemonstrates that, use of fuzzy linear programming inmultireservoir system optimization presents a potentialalternative to get the steady state solution with a lot lesseffort than classical stochastic dynamic programming.
fuzzy mathematical programming multireservoir system optimization steady state solution