Authors

Abstract

As a bridge connecting agricultural production and consumption, the circulation of agricultural products has the function of connecting supply and demand, guiding production and promoting consumption. However, the development of rural logistics in China is slow, and most logistics centers still rely on experience to plan the pick-up vehicle routings, resulting in long transport time and high cost. In order to improve the efficiency of pick-up and reduce transportation costs, a joint optimization model of cold-chain pick-up vehicle routing and cargo allocation for fresh agricultural products was proposed in this study. Soft time window constraint and three-dimensional loading constraints were considered, and the lowest pick-up cost was used as optimization goals in this model. In addition, adaptive large neighborhood search algorithm (ALNS) and heuristic depth-first search algorithm (HDFS) were combined to solve the model. A case study of Kunming International Flower Auction Center was conducted to compare the schemes of pick-up vehicle routing before and after optimization. Results demonstrate that the pick-up cost after optimization decreases by 9.6 %, the number of vehicles decreases by one, the total volume utilization rate of vehicles increases by 23 %, and the total load utilization rate of vehicles increases by 15 %. This study provides a model reference and solution method for enterprise operators to formulate schemes of pick-up vehicle routing quickly and reasonably.

Abstract in Chinese

农产品流通作为连接农业生产和消费的桥梁，具有连接供需、引导生产、促进消费的功能。然而，中国农村物流发展缓慢，大多数物流中心仍然依靠经验来规划取货车辆路线，导致运输时间长，成本高。为了提高提货效率，降低运输成本，本文提出了一种生鲜农产品冷链集货车辆路径与货物配载联合优化模型。该模型考虑了软时间窗约束和三维装载约束，以最低集货成本为优化目标。此外，结合自适应大邻域搜索算法(ALNS)和启发式深度优先搜索算法(HDFS)对模型进行求解。以昆明国际花卉拍卖中心为例，对比优化前后的集货车辆路径方案。结果表明，优化后的集货成本降低9.6%，车辆数量减少1辆，车辆总容积利用率提高23%，车辆总载重利用率提高15%。本研究为企业运营者快速合理地制定集货车辆路线方案提供了模型参考和解决方法。