动态需求下的基于医药前置仓的选址-路径问题研究
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西南交通大学

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F253.4

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Research on Location-routing Problem of Pharmaceutical Pre-warehouse based on Dynamic Demand
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Southwest Jiaotong University

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    摘要:

    随着新冠疫情的发展,公众逐渐建立起通过互联网购买医药物品的习惯,发展高效绿色的医药配送模式迫在眉睫.通过建立考虑动态需求的选址-路径两阶段数学规划模型,解决了医药前置仓的选址规划和配送路径设计问题.采用NSGA-III算法对初始优化阶段和动态优化阶段分别求解,并用模糊聚类法筛选出最优方案作为动态优化阶段的初始状态.再与NSGA-II算法进行求解时间、Spacing、HRS和PR等指标的对比分析,可见NSGA-III的运行时间更快,解集分布更均匀,收敛效果更好.最后分别计算运输车辆种类和药房合作前置仓的固定成本总预算变化对成本、时间和碳排三个目标函数的影响,测试模型和算法的敏感性,说明第三方药品配送企业更适合使用中小型车辆完成配送任务,并设置相对充裕的选址预算.

    Abstract:

    As the COVID-19 pandemic evolves, the public has gradually established the habit of buying medical supplies through the Internet. It is urgent to develop efficient and green medicine distribution mode. A location-routing two-stage mathematical programming model considering dynamic demand was established to solve the problem of location planning and distribution route designing of pharmaceutical pre-warehouse. NSGA-III algorithm was used to solve the initial optimization stage and dynamic optimization stage respectively. The optimal scheme was selected by fuzzy clustering method as the initial state of dynamic optimization stage. Comparing with NSGA-II algorithm for time, Spacing, HRS and PR, NSGA-III runs faster, and gets more uniform solution set distribution and better convergence effect. Finally, the influence of the total budget change of fixed cost on the three objective functions of cost, time and carbon emission were calculated to test the sensitivity of the model and algorithm. It indicates that the third-party drug delivery enterprises are more suitable to use small or medium-sized vehicles to complete the delivery task and set relatively abundant location budget.

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历史
  • 收稿日期:2021-09-21
  • 最后修改日期:2022-03-10
  • 录用日期:2022-03-15
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