A Decision-Oriented Fuzzy Multi-Objective Crop Planning Model With Α-Cut Sensitivity Across Farm Sizes
DOI:
https://doi.org/10.29284/ch4skn60Keywords:
Fuzzy multi-objective linear programming (FMOLP), Baghpat district, Production planning, LINGO 20.0, α-cut level.Abstract
Agricultural crop planning involves several competing goals and is intrinsically influenced by uncertainties stemming from volatile market prices, inconsistent yields, and resource limitations. Conventional linear programming methods depend on exact parameter values, therefore inadequately reflecting actual agricultural decision-making contexts. This work presents a decision-oriented fuzzy multi-objective linear programming (FMOLP) approach to optimize crop planning amidst uncertainty. The model concurrently optimizes agricultural output and profitability while explicitly integrating family-level food security needs as binding restrictions. Uncertainty in production coefficients, profitability, and resource availability is represented using triangular fuzzy numbers and addressed with an α-cut based methodology. The suggested approach differentiates itself from most current fuzzy crop planning research by extending the best solution over several farm-size categories, from marginal to large holdings, thereby improving its practical usefulness. A dual sensitivity analysis regarding α-cut levels (0.1–0.9) and satisfaction degree is performed to evaluate the robustness of the resulting solutions and to provide insights into optimistic and conservative decision-making strategies. The model's relevance is shown by a case study of the Baghpat district in India, using region-specific agronomic data. The findings validate that the suggested fuzzy framework produces consistent and dependable crop distribution choices under uncertainty, making it an effective decision-support instrument for agricultural planners and policymakers.
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