Water Resources Management

, Volume 14, Issue 6, pp 457–472

Multireservoir System Optimization using Fuzzy Mathematical Programming


DOI: 10.1023/A:1011117918943

Cite this article as:
Jairaj, P.G. & Vedula, S. Water Resources Management (2000) 14: 457. doi:10.1023/A:1011117918943


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 

Copyright information

© Kluwer Academic Publishers 2000

Authors and Affiliations

  1. 1.Department of Civil EngineeringIndian Institute of ScienceBangaloreIndia
  2. 2.College of EngineeringDepartment of Civil EngineeringTrivandrumIndia
  3. 3.Department of Civil EngineeringIndianInstitute of ScienceBangaloreIndia

Personalised recommendations