Scholarlink

<p>Achieving sustainability in agri-food supply chains faces challenges like water scarcity, production volatility, and price fluctuations. This study proposes a climate-smart framework integrating fuzzy logic-based crop planning with large-scale water-land allocation to enhance resilience and efficiency. It introduces a water worth tariff based on the De Martonne aridity index to optimize water use and promote sustainable irrigation. The model leverages geographical diversity and staggered planting cycles for complementary cultivation and market integration, improving productivity and resource efficiency. Designed for large-scale implementation via national farmers’ associations, it optimizes provincial production, storage, and transportation while minimizing costs and resource use under uncertainty, using fuzzy triangular numbers. Constraints address crop perishability and minimum farmer income, tackling socio-economic and logistical concerns. Applied to potato, onion, and tomato farming across 30 Iranian provinces with 2025 projections, the model, solved via CPLEX, shows planting-to-harvesting costs dominate (&gt; 95% of total expenses), emphasizing cost-reduction needs. Water tariffs, though minor, incentivize sustainable practices. Fuzzy analysis indicates optimistic parameter estimates improve feasibility, affecting costs and efficiency. The model aligns with cultivation trends, offering recommendations for transportation and storage infrastructure. Fostering collaboration among farmers, associations, wholesalers, and markets enhances agri-food supply chain sustainability amid environmental and economic pressures.</p>

错误：搜索内容不能为空，请输入英文关键词
错误：关键词超出字数限制，请精简
高级检索

A fuzzy framework for integrated large-scale agri-food supply chain and water-land allocation: evidence for scaled-up water-sustainable crop plans

  • 期刊论文

  • 发表日期：

    2025年12月21日

查看全文
  • Amir Hajimirzajan,
  • Saeid Nasrollahi,
  • Somayeh Emami,
  • Vahid Ettehadi

摘要

Achieving sustainability in agri-food supply chains faces challenges like water scarcity, production volatility, and price fluctuations. This study proposes a climate-smart framework integrating fuzzy logic-based crop planning with large-scale water-land allocation to enhance resilience and efficiency. It introduces a water worth tariff based on the De Martonne aridity index to optimize water use and promote sustainable irrigation. The model leverages geographical diversity and staggered planting cycles for complementary cultivation and market integration, improving productivity and resource efficiency. Designed for large-scale implementation via national farmers’ associations, it optimizes provincial production, storage, and transportation while minimizing costs and resource use under uncertainty, using fuzzy triangular numbers. Constraints address crop perishability and minimum farmer income, tackling socio-economic and logistical concerns. Applied to potato, onion, and tomato farming across 30 Iranian provinces with 2025 projections, the model, solved via CPLEX, shows planting-to-harvesting costs dominate (> 95% of total expenses), emphasizing cost-reduction needs. Water tariffs, though minor, incentivize sustainable practices. Fuzzy analysis indicates optimistic parameter estimates improve feasibility, affecting costs and efficiency. The model aligns with cultivation trends, offering recommendations for transportation and storage infrastructure. Fostering collaboration among farmers, associations, wholesalers, and markets enhances agri-food supply chain sustainability amid environmental and economic pressures.