Hesitant Intuitionistic fuzzy Approach in Optimal Irrigation Planning in India

The hesitant intuitionistic fuzzy optimization approach optimizes multi-objective optimization problems under uncertainty and hesitation; and reflects the practical aspects of better decision-making. In the present study, a new optimization approach, Hesitant intuitionistic fuzzy optimization (HIFO), has been proposed for optimal cropping pattern in the Kakrapar Right Bank Main Canal command area of Ukai Kakrapar Water Resources Project in India. The HIFO multi-objective fuzzy linear programming (HIFO MOFLP) solution includes three objectives, namely, maximization of net irrigation benefits (NB), maximization of employment generation (EG) and minimization of cost of cultivation (CC), with appropriate sets of constraints. The performance of the aforesaid model is assessed in terms of irrigation intensity, degree of acceptance (α), degree of rejection (β) for inflows corresponding to 75% probability of exceedance. The irrigation intensity from the proposed HIFO MOFLP model has been found to be 85.84 %, while NIB, EG and CC from the proposed model are 5559.32 million Rs, 14824.01-thousand-man days and 3454.37 million Rs, respectively with α = 0.65 and β = 0.22. The proposed HIFO MOFLP model has been compared with IFO MOFLP approach given by Pawar et al. (2020) for the same command area and found to give improved results in terms of the irrigation intensity of command area and objective function values. The current study demonstrates that, how hesitant fuzzy membership function and non-membership function can be applied to deal with uncertainty and hesitation for a real-world problem.