目的 针对生鲜产品冷链配送环节存在的配送成本高、产品易腐坏等问题,研究考虑新鲜度的生鲜冷链物流同时取送货车辆路径优化。方法 首先考虑同时取送货的场景,以及生鲜产品在不同场景下的新鲜度衰减速度,以车辆使用成本、货损成本、时间惩罚成本之和最小为目标,建立考虑新鲜度的生鲜冷链物流同时取送货车辆路径优化模型;其次,基于此模型,设计一种带大邻域搜索思想的头脑风暴算法（Brain storm optimization with large neighborhood search algorithm,BSO-LNS）进行求解;然后,通过与CPLEX求解器、遗传算法的对比分析,验证所建模型的合理性及求解算法的有效性;最后,求解实际冷链物流企业的算例,验证本文模型在实际冷链物流配送中的应用价值。结果 基于不同规模的算例,与CPLEX求解器、遗传算法相比,所设计的算法的求解效果更好,同时其求解速度更快。结论 所提模型、算法可有效减少生鲜产品品质损耗,同时兼顾对总成本的控制,进而为生鲜物流企业提供了方法参考和决策依据。
Abstract
The work aims to study the vehicle routing problem with simultaneous pickup and delivery for fresh food cold chain logistics taking into account product freshness, so as to solve the shortcomings in the cold chain distribution of fresh products, such as high distribution costs and product spoilage. Firstly, the scenario of simultaneous pickup-delivery was considered, along with the freshness decay rates of fresh products under different conditions. With the objective of minimizing the sum of vehicle usage costs, product damage costs, and time penalty costs, an optimization model for vehicle routing with simultaneous pickup-delivery in fresh food cold chain logistics that took into account product freshness was established. Secondly, based on this model, a Brain Storm Optimization with Large Neighborhood Search algorithm (BSO-LNS) was designed to solve the problem. Then, by comparing with the CPLEX solver and the genetic algorithm, the rationality of the model and the effectiveness of the algorithm were verified. Finally, the example of the actual cold chain logistics enterprise was solved to verify the application value of the model in the actual cold chain logistics distribution. Based on examples of different scales, and compared with the CPLEX solver and the genetic algorithm, it was proved that the designed algorithm had a better rationality and a faster speed. In conclusion, the proposed model and algorithm can effectively reduce the quality loss of fresh products, improve customer satisfaction, and take into account the control of total cost, so as to provide method reference and decision-making basis for fresh logistics enterprises.
关键词
车辆路径问题 /
同时取送货 /
头脑风暴算法 /
冷链物流
Key words
vehicle routing problem /
simultaneous pickup-delivery /
brain storm optimization /
cold chain logistics
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基金
国家社会科学基金一般项目（24FGLB055）; 辽宁省社会科学规划基金（L20CGL012）
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