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B. P. Shrestha, L. Duckstein and E. Z. Stakhiv, “A Fuzzy Rule Based Reservoir Operation,” Journal of Water Resource Management, Vol. 122, No.3, 1996, pp 262-269.

has been cited by the following article:

  • TITLE: Derivation of Multipurpose Single Reservoir Release Policies with Fuzzy Constraints

    AUTHORS: Dattatray G. Regulwar, Ravindra U. Kamodkar

    KEYWORDS: Fuzzy Logic, Linear Programming, Optimization, Reservoir Operation, Uncertainty

    JOURNAL NAME: Journal of Water Resource and Protection, Vol.2 No.12, December 30, 2010

    ABSTRACT: Recent research modeling uncertainty in water resource systems has highlighted the use of fuzzy logic based approaches. The uncertainties in water resource systems include fuzziness, subjectivity, imprecision and lack of adequate data. In this paper we focus on Fuzzy Linear Programming (FLP) problem for reservoir opera- tion with fuzzy objectives function and fuzzy constraints. Uncertainty in reservoir operation parameters such as reservoir storages, releases for irrigation, releases for hydropower production, irrigation demands, and power demands are considered by treating them as a fuzzy set. This study is devoted to the identification of optimal operating policy using three different models. A fuzzy linear programming reservoir operation models are developed within a linear programming framework. These models are applied to a case study of Jayakwadi reservoir stage -II, Maharashtra State, India with the objective of maximization of releases for irrigation and hydropower. Fuzzy set theory is used to model imprecision in various parameters by developing three models. First model considers fuzzy resources, second model is with fuzzy technological coefficients and third model considers both, fuzzy technological coefficients and fuzzy resources in linear programming framework. Fuzziness in objective function and in the constraints is quantified by a membership functions. These three models are solved to obtain compromise solution by simultaneously optimizing the fuzzified objectives and constraints. The degree of satisfaction is obtained by simultaneously optimizing the objectives are 0.53, 0.52 and 0.525 by three models respectively. The obtained result show that proposed methodology provides an effective and useful tool for reservoir operation where decision maker can decides to opt for a model depends on the imprecision involved in reservoir operation model parameters.