Sustainable Irrigation Planning with Imprecise Parameters under Fuzzy Environment

2012 ◽  
Vol 26 (13) ◽  
pp. 3871-3892 ◽  
Author(s):  
D. G. Regulwar ◽  
Jyotiba B. Gurav
Keyword(s):  
Irrigation Planning ◽  
Fuzzy Environment ◽  
Sustainable Irrigation ◽  
Imprecise Parameters

scholarly journals Multi-objective fuzzy optimization for sustainable irrigation planning

2020 ◽  
Vol 3 (1) ◽  
pp. 373-389 ◽  
Author(s):  
Jyotiba B. Gurav ◽  
D. G. Regulwar
Keyword(s):  
Crop Production ◽  
Fuzzy Optimization ◽  
Fuzzy Linear Programming ◽  
Cropping Pattern ◽  
Irrigation Planning ◽  
Multi Objective ◽  
Function Coefficient ◽  
Decision Variables ◽  
Optimal Cropping ◽  
Sustainable Irrigation

Abstract 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.

scholarly journals USE OF FUZZY MATHEMATICAL QUADRATIC PROGRAMMING APPROACH IN JOB EVALUATION

2021 ◽  
Vol 9 (2) ◽  
pp. 25-29
Author(s):  
Manoj Kumar Mandal ◽  
Arun Prasad Burnwal ◽  
Neelam Dubey ◽  
Om Prakash Dubey
Keyword(s):  
Fuzzy Logic ◽  
Quadratic Programming ◽  
Optimal Solution ◽  
Linear Formulation ◽  
Programming Approach ◽  
Evolution System ◽  
Job Evaluation ◽  
Related Information ◽  
Fuzzy Environment ◽  
Imprecise Parameters

Purpose of study: The current paper is the based on mathematical model of the job evolution system. Methodology: The proposed method is the fusion of quadratic programming and fuzzy logic where quadratic programming is used to optimize objective function with related constraints in the form of non-linear formulation. Fuzzy logic is used to control uncertainty related information by estimating imprecise parameters Main Finding: The optimal solution of the job evaluation based on fuzzy environment where goal is imprecise. Application of this study: It is used in the areas where information is not exact. The originality of this study: The novelty of the method is the fusion of quadratic programming and fuzzy logic.

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