Nasr Navid, Niaki Seyed Taghi Akhavan, Hussenzadek Kashan Ali, Seifbarghy Mehdi
School of Industrial & Mechanical Engineering, Islamic Azad University, Qazvin Branch, Tehran, Iran.
Department of Industrial Engineering, Sharif University of Technology, Tehran, Iran.
Environ Sci Pollut Res Int. 2021 Apr 23. doi: 10.1007/s11356-021-13718-8.
In the traditional agri-fresh food supply chain (AFSC), geographically dispersed small farmers transport their products individually to the market for sale. This leads to a higher transportation cost, which is the primary cause of farmers' low profitability. This paper formulates a traditional product movement problem in AFSC. First, the aggregate product movement model is combined with the vehicle routing model to redesign an existing AFSC (the ETKA Company; the most extensive domestic agri-fresh food supply chain in Iran) based on the available data. For the four-echelon, multi-period supply chain under investigation, a mixed integer linear programming (MILP) model is developed for the location-inventory-routing problem of perishable products via considering the clustering of farmers to minimize the total distribution cost. Considering the complexity of the problem, an efficient and effective "matheuristic" is introduced based on hybridizing the Lagrangian relaxation and genetic algorithm (GA). The solution obtained by the proposed "matheuristic" algorithm is robust and efficient in comparison with an exact solver, GA, and the Lagrangian relaxation approach individually. The comparison analysis reveals that the location-inventory-routing model is efficient, leading to a reduction in total distribution cost by 33% compared to the existing supply chain. Finally, the findings encourage further development and application of the proposed "matheuristic" to solve other complicated location-inventory-routing problems heuristically.
在传统的农产品新鲜食品供应链（AFSC）中，地理位置分散的小农户各自将其产品运输到市场销售。这导致运输成本较高，这是农民盈利能力低下的主要原因。本文阐述了AFSC中的传统产品运输问题。首先，将总产品运输模型与车辆路径模型相结合，根据现有数据重新设计了一个现有的AFSC（ETKA公司；伊朗国内最广泛的农产品新鲜食品供应链）。对于所研究的四级多周期供应链，通过考虑农户聚类，开发了一个混合整数线性规划（MILP）模型，用于易腐产品的选址-库存-路径问题，以最小化总配送成本。考虑到问题的复杂性，基于拉格朗日松弛和遗传算法（GA）的混合，引入了一种高效有效的“数学启发式算法”。与精确求解器、GA和拉格朗日松弛方法单独相比，所提出的“数学启发式算法”获得的解决方案具有鲁棒性和高效性。比较分析表明，选址-库存-路径模型是有效的，与现有供应链相比，总配送成本降低了33%。最后，研究结果鼓励进一步开发和应用所提出的“数学启发式算法”，以启发式地解决其他复杂的选址-库存-路径问题。
