用于灵活部署应急无人机的基于椭圆的定位方法

IF 6.2 2区 经济学 Q1 ECONOMICS Socio-economic Planning Sciences Pub Date : 2024-08-31 DOI:10.1016/j.seps.2024.102049
Jinqiu Zhao , Le Yu , Binglei Xie
{"title":"用于灵活部署应急无人机的基于椭圆的定位方法","authors":"Jinqiu Zhao ,&nbsp;Le Yu ,&nbsp;Binglei Xie","doi":"10.1016/j.seps.2024.102049","DOIUrl":null,"url":null,"abstract":"<div><p>Unmanned Aerial Vehicles (UAVs), or drones, are gaining attention in emergency response for their rapid mobility in dynamic scenarios. Constrained by limited endurance and payload, UAVs typically operate in a ”depot-customer-depot” paradigm. Thus, optimally locating multiple depots is critical to achieving operational efficiency and flexibility. Traditional location models, which rely on circular coverage, fail to capture the actual reachable area for UAV round-trips between multiple depots within a given endurance range. This drawback restricts deployment flexibility or results in excessive redundancy, even making it impractical. To address this limitation, we introduce an ellipse-based locating method for flexible UAV deployment, inspired by UAV reachability and process flexibility in manufacturing. This approach attempts to optimize the redundancy of multi-depot coverage for demand points to achieve a better balance between deployment flexibility and resource requirements. To tackle the model’s computational challenge, we present an improved Benders decomposition algorithm that speeds up the solution process by analytically addressing subproblems and implementing dominance rules to manage the master problem’s size. Simulations show that the proposed model greatly improves the ability to handle uncertainties by incorporating slight redundancy in emergency resources, and the fulfillment rate of demand fluctuations is increased by 5%–20%, which shows the superiority of enhancing the mobility and flexibility of UAV deployment.</p></div>","PeriodicalId":22033,"journal":{"name":"Socio-economic Planning Sciences","volume":"96 ","pages":"Article 102049"},"PeriodicalIF":6.2000,"publicationDate":"2024-08-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"An ellipse-based locating method for flexible deployment of emergency UAVs\",\"authors\":\"Jinqiu Zhao ,&nbsp;Le Yu ,&nbsp;Binglei Xie\",\"doi\":\"10.1016/j.seps.2024.102049\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>Unmanned Aerial Vehicles (UAVs), or drones, are gaining attention in emergency response for their rapid mobility in dynamic scenarios. Constrained by limited endurance and payload, UAVs typically operate in a ”depot-customer-depot” paradigm. Thus, optimally locating multiple depots is critical to achieving operational efficiency and flexibility. Traditional location models, which rely on circular coverage, fail to capture the actual reachable area for UAV round-trips between multiple depots within a given endurance range. This drawback restricts deployment flexibility or results in excessive redundancy, even making it impractical. To address this limitation, we introduce an ellipse-based locating method for flexible UAV deployment, inspired by UAV reachability and process flexibility in manufacturing. This approach attempts to optimize the redundancy of multi-depot coverage for demand points to achieve a better balance between deployment flexibility and resource requirements. To tackle the model’s computational challenge, we present an improved Benders decomposition algorithm that speeds up the solution process by analytically addressing subproblems and implementing dominance rules to manage the master problem’s size. Simulations show that the proposed model greatly improves the ability to handle uncertainties by incorporating slight redundancy in emergency resources, and the fulfillment rate of demand fluctuations is increased by 5%–20%, which shows the superiority of enhancing the mobility and flexibility of UAV deployment.</p></div>\",\"PeriodicalId\":22033,\"journal\":{\"name\":\"Socio-economic Planning Sciences\",\"volume\":\"96 \",\"pages\":\"Article 102049\"},\"PeriodicalIF\":6.2000,\"publicationDate\":\"2024-08-31\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Socio-economic Planning Sciences\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0038012124002489\",\"RegionNum\":2,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"ECONOMICS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Socio-economic Planning Sciences","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0038012124002489","RegionNum":2,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ECONOMICS","Score":null,"Total":0}
引用次数: 0

摘要

无人驾驶飞行器(UAV)或无人机因其在动态场景中的快速机动性,在应急响应中日益受到关注。受限于有限的续航时间和有效载荷,无人机通常以 "仓库-客户-仓库 "的模式运行。因此,对多个仓库进行优化定位对于实现运营效率和灵活性至关重要。传统的定位模型依赖于圆形覆盖范围,无法捕捉到无人机在给定续航时间范围内往返多个仓库的实际可达区域。这一缺点限制了部署的灵活性,或导致过多的冗余,甚至使部署变得不切实际。为了解决这一局限性,我们从无人机的可达性和制造过程的灵活性中汲取灵感,为无人机的灵活部署引入了一种基于椭圆的定位方法。这种方法试图优化需求点的多点覆盖冗余度,从而在部署灵活性和资源需求之间实现更好的平衡。为了解决该模型的计算难题,我们提出了一种改进的本德斯分解算法,通过分析处理子问题和实施支配规则来管理主问题的规模,从而加快求解过程。仿真结果表明,所提出的模型通过在应急资源中加入轻微冗余,极大地提高了处理不确定性的能力,需求波动的满足率提高了 5%-20%,显示了增强无人机部署的机动性和灵活性的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
An ellipse-based locating method for flexible deployment of emergency UAVs

Unmanned Aerial Vehicles (UAVs), or drones, are gaining attention in emergency response for their rapid mobility in dynamic scenarios. Constrained by limited endurance and payload, UAVs typically operate in a ”depot-customer-depot” paradigm. Thus, optimally locating multiple depots is critical to achieving operational efficiency and flexibility. Traditional location models, which rely on circular coverage, fail to capture the actual reachable area for UAV round-trips between multiple depots within a given endurance range. This drawback restricts deployment flexibility or results in excessive redundancy, even making it impractical. To address this limitation, we introduce an ellipse-based locating method for flexible UAV deployment, inspired by UAV reachability and process flexibility in manufacturing. This approach attempts to optimize the redundancy of multi-depot coverage for demand points to achieve a better balance between deployment flexibility and resource requirements. To tackle the model’s computational challenge, we present an improved Benders decomposition algorithm that speeds up the solution process by analytically addressing subproblems and implementing dominance rules to manage the master problem’s size. Simulations show that the proposed model greatly improves the ability to handle uncertainties by incorporating slight redundancy in emergency resources, and the fulfillment rate of demand fluctuations is increased by 5%–20%, which shows the superiority of enhancing the mobility and flexibility of UAV deployment.

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
Socio-economic Planning Sciences
Socio-economic Planning Sciences OPERATIONS RESEARCH & MANAGEMENT SCIENCE-
CiteScore
9.40
自引率
13.10%
发文量
294
审稿时长
58 days
期刊介绍: Studies directed toward the more effective utilization of existing resources, e.g. mathematical programming models of health care delivery systems with relevance to more effective program design; systems analysis of fire outbreaks and its relevance to the location of fire stations; statistical analysis of the efficiency of a developing country economy or industry. Studies relating to the interaction of various segments of society and technology, e.g. the effects of government health policies on the utilization and design of hospital facilities; the relationship between housing density and the demands on public transportation or other service facilities: patterns and implications of urban development and air or water pollution. Studies devoted to the anticipations of and response to future needs for social, health and other human services, e.g. the relationship between industrial growth and the development of educational resources in affected areas; investigation of future demands for material and child health resources in a developing country; design of effective recycling in an urban setting.
期刊最新文献
Modelling global fossil CO2 emissions with a lognormal distribution Variable RTS in hierarchical network DEA: Enhancing efficiency in higher education systems I like participatory museums but, how much? Embedding demand-side value in assessing strategies A hybrid MCDM framework for assessing urban competitiveness: A case study of European cities Low-carbon route optimization model for multimodal freight transport considering value and time attributes
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1