社区疫情排查的智能优化调度方法

陈鑫; 吴佳宇; 吴雪; 张敏霞; 郑宇军

doi:10.11959/j.issn.2096-6652.202014

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社区疫情排查的智能优化调度方法

学术论文 | 更新时间：2024-06-05

- 社区疫情排查的智能优化调度方法
- An intelligent optimization scheduling method for community patrolling and investigation in epidemic situations
- 智能科学与技术学报 2020年2卷第2期页码：126-134
- 作者机构：
  
  1. 杭州师范大学信息科学与工程学院，浙江杭州 311121
  2. 浙江工业大学计算机科学与技术学院，浙江杭州 310023
- 作者简介：
  
  [ "陈鑫（1997- ），女，杭州师范大学信息科学与工程学院硕士生，主要研究方向为智能优化算法" ]
  [ "吴佳宇（1996- ），女，浙江工业大学计算机科学与技术学院硕士生，主要研究方向为智能优化调度" ]
  [ "吴雪（1996- ），女，浙江工业大学计算机科学与技术学院硕士生，主要研究方向为智能优化调度" ]
  [ "张敏霞（1968- ），女，博士，浙江工业大学计算机科学与技术学院副教授，主要研究方向为智能交通和智慧物流" ]
  [ "郑宇军（1979- ），男，博士，杭州师范大学信息科学与工程学院教授，主要研究方向为智能优化计算" ]
- 基金信息：
  
  国家自然科学基金资助项目;The National Natural Science Foundation of China(61872123);浙江省自然科学基金资助项目;The Natural Science Foundation of Zhejiang Province(LR20F030002)
- DOI：10.11959/j.issn.2096-6652.202014
  中图分类号： TP391.1
- 网络出版日期：2020-06，
  
  纸质出版日期：2020-06-20
- 稿件说明：
移动端阅览
陈鑫, 吴佳宇, 吴雪, 等. 社区疫情排查的智能优化调度方法[J]. 智能科学与技术学报, 2020,2(2):126-134.

Xin CHEN, Jiayu WU, Xue WU, et al. An intelligent optimization scheduling method for community patrolling and investigation in epidemic situations[J]. Chinese journal of intelligent science and technology, 2020, 2(2): 126-134.
陈鑫, 吴佳宇, 吴雪, 等. 社区疫情排查的智能优化调度方法[J]. 智能科学与技术学报, 2020,2(2):126-134. DOI： 10.11959/j.issn.2096-6652.202014.

Xin CHEN, Jiayu WU, Xue WU, et al. An intelligent optimization scheduling method for community patrolling and investigation in epidemic situations[J]. Chinese journal of intelligent science and technology, 2020, 2(2): 126-134. DOI： 10.11959/j.issn.2096-6652.202014.

摘要

在应对突发重大传染病时，社区防控是整个社会疫情防控的重要一环。在新型冠状病毒肺炎疫情社区防控实践经验的基础上，提出一个社区疫情排查调度问题的数学模型，根据相关疫情防控信息为社区重点住户估算风险指数，并在此基础上将重点住户分配给各个排查工作小组，为每个小组设定排查路线，从而尽可能高效地完成各项排查任务。为求解该问题，提出一种混合智能优化调度算法，它基于水波优化的启发式策略搜索解空间，并混合了两种局部搜索策略来提高解的精度，形成初步调度方案。在调度方案的实施过程中，如果排查到某个对象有特殊情况需要处置，算法将对方案进行动态调整，以适应变化后的排查任务。在浙江省多个社区排查的实际案例问题上的计算结果验证了方法的有效性。

Abstract

Community plays an important role in epidemic prevention and control in the society.Based on the practical experience of community prevention and control of the novel corona virus pneumonia

a community patrolling and investigation scheduling problem in epidemic situations was presented

which estimated a risk value for each high-risk household based on epidemic-related information

and then scheduled the community staffs to patrol and investigate the high-risk households as efficiently as possible.To solve this problem

a hybrid intelligent optimization scheduling algorithm was proposed

which explored the solution space based on the search strategy of the water wave optimization (WWO) met heuristic and improved solution accuracies using two local search strategies.Whenever an exceptional case was detected during the patrolling and investigation

the solution was dynamically adapted to the changed situation.Computational results on the real-world cases of community patrolling and investigation in Zhejiang Province

China demonstrate the effectiveness and efficiency of the proposed method.

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references

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