目的 针对药品物流配送中因订单拆分需求与时间窗约束导致的物流运营成本高、客户服务效率低等问题,提出考虑订单拆分与时间窗约束的药品物流配送车辆路径优化策略。方法 首先,构建了包含车辆配送成本、车辆维护与租赁成本、时间窗惩罚成本及订单拆分成本的最小化物流运营总成本和车辆使用数的双目标优化模型。其次,提出一种融合订单拆分策略的改进自适应大邻域搜索算法求解模型。通过设计拆分相关性破坏算子与修复算子,以增强算法的优化能力,并通过融合模拟退火接受准则的自适应权重调整策略提升了算法的全局寻优能力,同时设计了全局车辆共享策略实现配送车辆的共享调度;再次,通过与非支配排序遗传算法-Ⅱ、多目标遗传算法和多目标蚁群算法的对比分析,验证了所提模型和算法的有效性;最后,结合实例数据比较分析了不同车辆共享模式与不同订单拆分模式下的优化方案,并探讨了物流运营总成本和配送车辆使用数等相关指标的变化情况。结果 优化后的车辆路径方案使配送车辆使用数减少了7,物流总运营成本节省了47.63%。结论 采用本文提出的模型、算法和策略可合理规划药品物流配送路径,降低运营总成本和车辆使用数,进而为考虑订单拆分和时间窗的药品物流配送车辆路径问题提供方法参考和理论支撑。
Abstract
The work aims to propose a vehicle routing optimization strategy for pharmaceutical logistics distribution that takes into account order splitting and time window constraints, to deal with the high distribution costs and low customer service efficiency in pharmaceutical logistics distribution due to the order splitting demands and time window constraints. First, a bi-objective optimization model was constructed, which minimized the total logistics cost and the number of used vehicles, including vehicle distribution cost, vehicle maintenance cost, leasing cost, time window penalty cost, and order splitting cost. Second, an improved adaptive large neighborhood search algorithm integrating order splitting strategies was proposed to solve the model. Splitting-related disruption operators and splitting order priority repair operators were designed to enhance the optimization ability. The adaptive weight adjustment mechanism of the simulated annealing acceptance criterion was integrated to improve the global optimization ability of the algorithm. At the same time, a global vehicle sharing strategy was designed to achieve the shared scheduling of delivery vehicles. Then, through a comparative analysis with the non-dominated sorting genetic algorithm-II, the multi-objective genetic algorithm and the multi-objective ant colony algorithm, the effectiveness of the proposed model and algorithm was verified. Finally, based on the real-world data, the optimized schemes under different vehicle sharing modes and different order splitting modes were compared and analyzed, and the changes in related indicators such as the total logistics operating cost and the number of used vehicles were discussed. The optimized vehicle routing scheme reduced the number of used vehicles by 7 and saved 47.63% of the total logistics operating cost. The proposed model, algorithm and strategy can reasonably plan the delivery vehicle routes, reduce the total operating cost and vehicle usage, and provide method references and theoretical support for solving the vehicle routing problem of pharmaceutical logistics delivery considering order splitting and time windows.
关键词
药品物流 /
车辆路径问题 /
订单拆分 /
修复算子 /
改进自适应大邻域搜索算法
Key words
pharmaceutical logistics /
vehicle routing problem /
order splitting /
repair operator /
improved adaptive large neighborhood search algorithm
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基金
国家自然科学基金项目（72371044）; 重庆市自然科学基金面上项目（CSTB2025NSCQ-GPX0848）; 重庆市教委科学技术重大项目（KJZD-M202300704）; 重庆市高等教育教学改革研究重大项目（251030）; 重庆交通大学“揭榜挂帅”项目（Z36250002）; 重庆市教委人文社科研究项目（26SKJD096）; 重庆市研究生科研创新项目（CYS25571）
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