Multi-objective fuzzy optimization for sustainable irrigation planning | Zendy

Jyotiba B. Gurav | Zendy; D. G. Regulwar | Zendy

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Multi-objective fuzzy optimization for sustainable irrigation planning

Author(s) -

Jyotiba B. Gurav,

D. G. Regulwar

Publication year - 2020

Publication title -

h2open journal

Language(s) - English

Resource type - Journals

ISSN - 2616-6518

DOI - 10.2166/h2oj.2020.032

Subject(s) - sustainability , fuzzy logic , irrigation , production (economics) , cropping , agricultural engineering , linear programming , work (physics) , crop production , computer science , mathematical optimization , mathematics , engineering , agriculture , economics , geography , mechanical engineering , ecology , archaeology , artificial intelligence , biology , macroeconomics

The objective of the present work is to determine an optimal cropping pattern under uncertainty, which maximizes four objectives simultaneously, including net benefits (NBF), crop production (CPD), employment generation (EGN) and manure utilization (MUT). Except the objective of maximizing the NBF, the other objectives are related to sustainability. To deal with uncertainty, a multi-objective fuzzy linear programming (MOFLP) model has developed along with fuzziness in decision parameters (objective function coefficient, cost coefficients, technological coefficients and resources) and decision variables (area to be irrigated under each crop in each season) and applied the same to Jayakwadi Project Stage-I, Maharashtra, India. The present study is in the form of a successful attempt to deal with irrigation planning associated with sustainability and uncertainty.

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