系统仿真学报 ›› 2022, Vol. 34 ›› Issue (09): 1988-1998.doi: 10.16182/j.issn1004731x.joss.21-0362

• 仿真建模理论与方法 • 上一篇    下一篇

考虑紧迫度的应急物资调度及粒子群算法求解

张莉(), 张惠珍(), 刘冬, 陆雨欣   

  1. 上海理工大学 管理学院,上海  200093
  • 收稿日期:2021-04-21 修回日期:2021-08-08 出版日期:2022-09-18 发布日期:2022-09-23
  • 通讯作者: 张惠珍 E-mail:15871731805@163.com;zhzzywz@163.com
  • 作者简介:张莉(1995-),女,硕士生,研究方向为智能优化。E-mail:15871731805@163.com
  • 基金资助:
    国家自然科学基金(71401106);教育部人文社会科学基金(16YJA630037)

Particle Swarm Algorithm for Solving Emergency Material Dispatch Considering Urgency

Li Zhang(), Huizhen Zhang(), Dong Liu, Yuxin Lu   

  1. School of Management, University of Shanghai for Science and Technology, Shanghai 200093, China
  • Received:2021-04-21 Revised:2021-08-08 Online:2022-09-18 Published:2022-09-23
  • Contact: Huizhen Zhang E-mail:15871731805@163.com;zhzzywz@163.com

摘要:

重大公共卫生事件爆发初期,医疗物资消耗迅速,供给严重不足,为了合理高效地分配医疗物资,开展应急医疗物资配送问题研究。引入熵权法确定需求点的需求紧迫度,优先配送紧迫度高的需求点,在此基础上尽可能地使配送路径最短,实现构建基于物资需求点紧迫度不同前提下的需求可拆分的多目标应急医疗物资调度模型;并使用动态惯性权重和增加粒子扰动项等策略对粒子群算法进行改进用于求解模型。结果表明:该方法可高效解决资源紧缺情况下应急物资调配及车辆路径方案生成问题。

关键词: 熵权法, 需求紧迫度, 应急医疗物资调度, 多目标粒子群算法, 路径规划

Abstract:

In the early stage of major public health events, medical supplies are rapidly consumed and severely insufficient. In order to distribute medical supplies in a reasonable and efficient manner, research on the distribution of emergency medical materials is carried out. The entropy method is introduced to determine the urgency of demand points, thus could give priority to the demand points with high urgency and make the distribution routing as short as possible on that basis to realize the construction of a split delivery and multi-objective emergency medical materials scheduling model based on different urgency of demand points. Meanwhile the particle swarm optimization algorithm is improved by using dynamic intertia weight and adding particle disturbance term to solve the model. The results show that this method can efficiently solve the problem of emergency material allocation and vehicle routing plan generation under the condition of resource shortage.

Key words: entropy method, demand urgency, emergency medical supplies scheduling, multi-objective particle swarm algorithm, path planning

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