王勇,谢红霞,苟梦圆,赵小琴.基于车辆共享的生鲜商品多车舱装载配送路径优化问题[J].包装工程,2025,(3):210-220.
WANG Yong,XIE Hongxia,GOU Mengyuan,ZHAO Xiaoqin.Fresh Commodity Multi-compartment Loading Distribution Routing Optimization Problem Based on Vehicle Sharing[J].Packaging Engineering,2025,(3):210-220. |
| 基于车辆共享的生鲜商品多车舱装载配送路径优化问题 |
| Fresh Commodity Multi-compartment Loading Distribution Routing Optimization Problem Based on Vehicle Sharing |
| 投稿时间：2024-09-24 |
| DOI：10.19554/j.cnki.1001-3563.2025.03.025 |
| 中文关键词: 生鲜商品配送 多车舱装载 车辆共享 车辆路径问题 蚁群-禁忌搜索混合算法 |
| 英文关键词: fresh commodity distribution multi-compartment loading vehicle sharing vehicle routing problem hybrid ACO-TS algorithm |
| 基金项目:国家自然科学基金(72371044，71871035);重庆市教委科学技术研究重大项目(KJZD-M202300704);巴渝学者青年项目(YS2021058);重庆市研究生科研创新项目(CYS240511) |
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| 中文摘要: |
| 目的 针对生鲜商品物流配送优化研究在车辆共享调度和多车舱装载配送合理结合方面存在的不足，研究了基于车辆共享的生鲜商品多车舱装载配送路径优化问题。方法 首先，结合生鲜商品温控条件和多车舱装载约束，建立了生鲜商品多车舱装载配送的物流运营总成本最小化的数学模型;其次，设计了蚁群-禁忌搜索混合算法求解模型，并引入选择性赋予机制和车辆共享策略以提高算法的寻优性能;然后，通过与粒子群算法、大邻域搜索算法和差分进化算法的对比分析，验证了所提模型和算法的有效性;最后，结合实例，比较分析了生鲜商品多车舱装载配送优化前后的相关指标，提出车辆路径优化方案，并从服务时间段划分和车舱容量选择2方面进行敏感性分析。结果 优化后的物流运营总成本降低了43.53%，平均装载率提高了25%，并验证了合理划分服务时间段和选择车舱容量可有效提高车辆平均装载率和降低生鲜商品价值损失。结论 所提模型、算法和车辆共享策略可合理规划配送路径，降低运营总成本和生鲜商品价值损失，进而为基于车辆共享的生鲜商品多车舱装载配送路径优化问题提供方法参考和理论支撑。 |
| 英文摘要: |
| The work aims to explore the fresh commodity multi-compartment loading distribution routing optimization problem based on vehicle sharing to deal with the deficiencies of fresh commodities logistics distribution optimization research in the reasonable combination of vehicle sharing scheduling and multi-compartment loading distribution. First, a mathematical model to minimize the operating cost was established based on the temperature control conditions of fresh commodities and the loading constraints of the multi-compartment. Second, a hybrid ant colony-tabu search algorithm was designed to solve the model, and a selective assignment mechanism and a vehicle-sharing strategy were introduced to improve the optimization capability. Then, the effectiveness of the proposed model and algorithm was verified through comparative analysis with particle swarm optimization, large neighborhood search algorithm, and differential evolution algorithm. Finally, combined with examples, relevant indexes before and after optimization were compared and analyzed, a vehicle route optimization scheme was proposed, and a sensitivity analysis of compartment capacity was conducted. The optimized operating cost was reduced by 43.53%, the average loading rate was increased by 25%, and the reasonable segmentation of service period and selection of compartment capacity could effectively improve the average loading rate of vehicles and reduce the value loss of fresh commodities. The proposed model, algorithm, and vehicle-sharing strategy can reasonably schedule the distribution route and reduce the operating cost and value loss of fresh commodity, which provides methodological references and theoretical supports for the fresh commodities multi-compartment loading distribution routing optimization based on vehicle sharing. |
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