疫苗接种政策的优化设计:纽芬兰和拉布拉多案例研究

IF 0.8 4区 管理学 Q4 OPERATIONS RESEARCH & MANAGEMENT SCIENCE
Faraz Khoshbakhtian , Hamidreza Validi , Mario Ventresca , Dionne Aleman
{"title":"疫苗接种政策的优化设计:纽芬兰和拉布拉多案例研究","authors":"Faraz Khoshbakhtian ,&nbsp;Hamidreza Validi ,&nbsp;Mario Ventresca ,&nbsp;Dionne Aleman","doi":"10.1016/j.orl.2024.107140","DOIUrl":null,"url":null,"abstract":"<div><p>This paper proposes pandemic mitigation vaccination policies for Newfoundland and Labrador (NL) based on two compact mixed integer programming (MIP) models of the distance-based critical node detection problem (DCNDP). Our main focus is on two variants of the DCNDP that seek to minimize the number of connections with lengths of at most one (1-DCNDP) and two (2-DCNDP). A polyhedral study for the 1-DCNDP is conducted, and new aggregated inequalities are provided for the 2-DCNDP. The computational experiments show that the 2-DCNDP with aggregated inequalities outperforms the one with disaggregated inequalities for graphs with a density of at least 0.5%. We also study the strategic vaccine allocation problem as a real-world application of the DCNDP and conduct a set of computational experiments on a simulated contact network of NL. Our computational results demonstrate that the DCNDP-based strategies can have a better performance in comparison with the real-world strategies implemented during COVID-19.</p></div>","PeriodicalId":54682,"journal":{"name":"Operations Research Letters","volume":"55 ","pages":"Article 107140"},"PeriodicalIF":0.8000,"publicationDate":"2024-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Optimal design of vaccination policies: A case study for Newfoundland and Labrador\",\"authors\":\"Faraz Khoshbakhtian ,&nbsp;Hamidreza Validi ,&nbsp;Mario Ventresca ,&nbsp;Dionne Aleman\",\"doi\":\"10.1016/j.orl.2024.107140\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>This paper proposes pandemic mitigation vaccination policies for Newfoundland and Labrador (NL) based on two compact mixed integer programming (MIP) models of the distance-based critical node detection problem (DCNDP). Our main focus is on two variants of the DCNDP that seek to minimize the number of connections with lengths of at most one (1-DCNDP) and two (2-DCNDP). A polyhedral study for the 1-DCNDP is conducted, and new aggregated inequalities are provided for the 2-DCNDP. The computational experiments show that the 2-DCNDP with aggregated inequalities outperforms the one with disaggregated inequalities for graphs with a density of at least 0.5%. We also study the strategic vaccine allocation problem as a real-world application of the DCNDP and conduct a set of computational experiments on a simulated contact network of NL. Our computational results demonstrate that the DCNDP-based strategies can have a better performance in comparison with the real-world strategies implemented during COVID-19.</p></div>\",\"PeriodicalId\":54682,\"journal\":{\"name\":\"Operations Research Letters\",\"volume\":\"55 \",\"pages\":\"Article 107140\"},\"PeriodicalIF\":0.8000,\"publicationDate\":\"2024-07-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Operations Research Letters\",\"FirstCategoryId\":\"91\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0167637724000762\",\"RegionNum\":4,\"RegionCategory\":\"管理学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"OPERATIONS RESEARCH & MANAGEMENT SCIENCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Operations Research Letters","FirstCategoryId":"91","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0167637724000762","RegionNum":4,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"OPERATIONS RESEARCH & MANAGEMENT SCIENCE","Score":null,"Total":0}
引用次数: 0

摘要

本文基于基于距离的关键节点检测问题(DCNDP)的两个紧凑型混合整数编程(MIP)模型,为纽芬兰和拉布拉多(NL)提出了大流行病缓解疫苗接种政策。我们的主要重点是 DCNDP 的两个变体,它们分别寻求最大限度减少长度为 1(1-DCNDP)和 2(2-DCNDP)的连接数。我们对 1-DCNDP 进行了多面体研究,并为 2-DCNDP 提供了新的集合不等式。计算实验表明,对于密度至少为 0.5% 的图,采用聚合不等式的 2-DCNDP 优于采用分解不等式的 2-DCNDP。我们还将战略疫苗分配问题作为 DCNDP 在现实世界中的应用进行了研究,并在 NL 的模拟接触网络上进行了一系列计算实验。我们的计算结果证明,与 COVID-19 期间实施的真实世界策略相比,基于 DCNDP 的策略具有更好的性能。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Optimal design of vaccination policies: A case study for Newfoundland and Labrador

This paper proposes pandemic mitigation vaccination policies for Newfoundland and Labrador (NL) based on two compact mixed integer programming (MIP) models of the distance-based critical node detection problem (DCNDP). Our main focus is on two variants of the DCNDP that seek to minimize the number of connections with lengths of at most one (1-DCNDP) and two (2-DCNDP). A polyhedral study for the 1-DCNDP is conducted, and new aggregated inequalities are provided for the 2-DCNDP. The computational experiments show that the 2-DCNDP with aggregated inequalities outperforms the one with disaggregated inequalities for graphs with a density of at least 0.5%. We also study the strategic vaccine allocation problem as a real-world application of the DCNDP and conduct a set of computational experiments on a simulated contact network of NL. Our computational results demonstrate that the DCNDP-based strategies can have a better performance in comparison with the real-world strategies implemented during COVID-19.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
Operations Research Letters
Operations Research Letters 管理科学-运筹学与管理科学
CiteScore
2.10
自引率
9.10%
发文量
111
审稿时长
83 days
期刊介绍: Operations Research Letters is committed to the rapid review and fast publication of short articles on all aspects of operations research and analytics. Apart from a limitation to eight journal pages, quality, originality, relevance and clarity are the only criteria for selecting the papers to be published. ORL covers the broad field of optimization, stochastic models and game theory. Specific areas of interest include networks, routing, location, queueing, scheduling, inventory, reliability, and financial engineering. We wish to explore interfaces with other fields such as life sciences and health care, artificial intelligence and machine learning, energy distribution, and computational social sciences and humanities. Our traditional strength is in methodology, including theory, modelling, algorithms and computational studies. We also welcome novel applications and concise literature reviews.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信