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<p>The agriculture sector plays a crucial role in a country’s development as it fulfils the basic needs of its population. Efficient crop selection and land allocation are essential for enhancing productivity and sustainability, yet resource constraints and uncertainties, such as water scarcity, fertilizer availability, and climate variability, pose significant challenges. This research develops a multi-objective linear model to optimize sustainable crop selection, land allocation, and intercropping, integrating economic and social objectives under uncertainties like water scarcity and climate variability. The model incorporates intercropping strategies and land type-specific constraints based on water availability, reflecting realistic agricultural conditions. It employs the augmented <i>ε</i><b>-</b>constraint method combined with lexicographic optimization to handle conflicting objectives, including profit, job opportunities, and yield. The study compares single cropping patterns with intercropping, considering three crops: ladyfinger, tomato, and round gourd, along with their intercropping combinations. The results reveal that intercropping ladyfinger with round gourds yields the highest profit and output, while intercropping tomatoes and ladyfinger involves more work hours. Labor is a critical crop-farming resource, contributing almost 53% to the total cost. Compared to traditional practices, the proposed approach improves overall revenue, labor utilization, and crop output, highlighting intercropping as a strategy to enhance productivity, profitability, and resource efficiency. The model provides valuable insights for farmers and agricultural policymakers to ensure food security, foster economic growth, and reduce unemployment.</p>

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Optimizing sustainable agricultural production under uncertainty: a multi-objective model for crop selection and land allocation

  • 期刊论文

  • 发表日期：

    2026年1月21日

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  • Musawer Zeb,
  • Waqas Ahmed,
  • Muhammad Moazzam,
  • Salman Sagheer Warsi,
  • Muhammad Salman Habib

摘要

The agriculture sector plays a crucial role in a country’s development as it fulfils the basic needs of its population. Efficient crop selection and land allocation are essential for enhancing productivity and sustainability, yet resource constraints and uncertainties, such as water scarcity, fertilizer availability, and climate variability, pose significant challenges. This research develops a multi-objective linear model to optimize sustainable crop selection, land allocation, and intercropping, integrating economic and social objectives under uncertainties like water scarcity and climate variability. The model incorporates intercropping strategies and land type-specific constraints based on water availability, reflecting realistic agricultural conditions. It employs the augmented ε-constraint method combined with lexicographic optimization to handle conflicting objectives, including profit, job opportunities, and yield. The study compares single cropping patterns with intercropping, considering three crops: ladyfinger, tomato, and round gourd, along with their intercropping combinations. The results reveal that intercropping ladyfinger with round gourds yields the highest profit and output, while intercropping tomatoes and ladyfinger involves more work hours. Labor is a critical crop-farming resource, contributing almost 53% to the total cost. Compared to traditional practices, the proposed approach improves overall revenue, labor utilization, and crop output, highlighting intercropping as a strategy to enhance productivity, profitability, and resource efficiency. The model provides valuable insights for farmers and agricultural policymakers to ensure food security, foster economic growth, and reduce unemployment.