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D. G. Regulwar

Researcher at Government College

Publications -  22
Citations -  318

D. G. Regulwar is an academic researcher from Government College. The author has contributed to research in topics: Fuzzy logic & Maximization. The author has an hindex of 9, co-authored 20 publications receiving 258 citations.

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Irrigation Planning Under Uncertainty—A Multi Objective Fuzzy Linear Programming Approach

TL;DR: Multi Objective Fuzzy Linear Programming (MOFLP) irrigation planning model is formulated for deriving the optimal cropping pattern plan for the case study of Jayakwadi project in the Godavari river sub basin in Maharashtra State, India.
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Differential Evolution Algorithm with Application to Optimal Operation of Multipurpose Reservoir

TL;DR: In this paper, an application of Differential Evolution (DE) for the optimal operation of multipurpose reservoir is presented. And the DE algorithm application is presented through Jayakwadi project stage-I, Maharashtra State, India.
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Fuzzy Approach Based Management Model for Irrigation Planning

TL;DR: In this article, the authors developed the irrigation planning model and applied the same in the form of Multi Objective Fuzzy Linear Programming (MOFLP) approach for crop planning in command area of Jayakwadi Project Stage I, Maharashtra State, India.
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Multi Objective Multireservoir Optimization in Fuzzy Environment for River Sub Basin Development and Management

TL;DR: A monthly Multi Objective Genetic Algorithm Fuzzy Optimization (MOGAFU-OPT) model for the present study is developed in ‘C’ Language and applied to a multireservoir system in Godavari river sub basin in Ma-harashtra State, India.
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Development of 3-D Optimal Surface for Operation Policies of a Multireservoir in Fuzzy Environment Using Genetic Algorithm for River Basin Development and Management

TL;DR: A Multi objective, Multireservoir operation model for maximization of irrigation releases and maximizations of hydropower production is proposed using Genetic Algorithm and fuzzified and simultaneously maximized by defining and then maximizing level of satisfaction (λ).