The multi-level location routing problem (MLLRP) is an extension of the capacitated location routing problem (CLRP). MLLRPs are considered a class of combinatorial optimization problems that arise in transportation applications, such as agricultural logistic planning. Along with concerns regarding the environmental harmfulness, recent studies have considered “green” logistics. This paper addressed a low environmental impact model for MLLRP by considering characteristics, emissions, and traffic congestion that have not appeared in the recent literature. The mathematical model was formulated to deal with a reverse flow problem, which was a real case that occurs in Thailand agriculture. We developed a hybrid metaheuristic algorithm to solve the MLLRP by integrating a variable neighborhood search (VNS) with an adaptive large neighborhood search (ALNS). The experimental results shown that the hybrid algorithm had clear advantages in the time consumption and quality of the solution. The extended study indicated that the proposed algorithm obtained competitive results compared with the previously published methods. The proposed practice is useful not only for the agricultural industry but also for other industries.

多级位置路由问题（MLLRP）是容量限制位置路由问题（CLRP）的扩展。MLLRP被认为是一类在运输应用中出现的组合优化问题，例如农业物流计划。除了对环境危害的关注之外，最近的研究还考虑了“绿色”物流。本文通过考虑近期文献中未出现的特征，排放和交通拥堵，为MLLRP提出了一个低环境影响模型。制定了数学模型来处理逆流问题，这是泰国农业中发生的真实情况。我们开发了一种混合元启发式算法，通过将可变邻域搜索（VNS）与自适应大邻域搜索（ALNS）集成来解决MLLRP。实验结果表明，该混合算法在解决方案的时间消耗和质量上具有明显的优势。扩展研究表明，与先前发表的方法相比，该算法获得了竞争性结果。提议的做法不仅对农业产业有用，而且对其他产业也有用。