C. Markarian, Peter Khallouf
{"title":"Online Metric Facility Service Leasing with Duration-Specific Dormant Fees","authors":"C. Markarian, Peter Khallouf","doi":"10.5220/0010668600003062","DOIUrl":null,"url":null,"abstract":"Inspired by the COVID-19 pandemic, a new online facility model, known as the Online Facility Service Leasing problem (OFSL), has been recently introduced. In OFSL, services at different (health) facility locations are leased for different durations and costs. Each service at each facility is associated with a dormant fee that needs to be paid for each day on which the service is not leased at the facility. Clients arrive over time, each requesting a number of services, and need to be served by connecting them to multiple facilities jointly offering the requested services. The aim is to decide which services to lease, when, and for how long, in order to serve all clients as soon as they appear with minimum costs of leasing, connecting, and dormant fees. In this paper, we study a generalization of OFSL in which we are additionally given a parameter d, such that, should the service be not leased for more than d consecutive days, a dormant fee is to be paid (d = 0 in the case of OFSL). We call this variant the Online Facility Service Leasing with Duration-Specific Dormant Fees (d-OFSL). We particularly focus on the metric version of the problem in which facilities and clients reside in the metric space. We refer to it as metric d-OFSL and design the first online algorithm for the problem. The latter is a deterministic algorithm based on a primal-dual approach. We measure its performance by comparing it to the optimal offline solution for all instances of the problem. This performance analysis is known as competitive analysis and is the standard to evaluate online algorithms. Copyright © 2021 by SCITEPRESS – Science and Technology Publications, Lda. All rights reserved","PeriodicalId":380008,"journal":{"name":"International Conference on Innovative Intelligent Industrial Production and Logistics","volume":"36 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1900-01-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"International Conference on Innovative Intelligent Industrial Production and Logistics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.5220/0010668600003062","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 1
在线计量设施服务租赁与特定期限的休眠费用
受新型冠状病毒感染症(COVID-19)的影响,最近出现了一种新的在线设施模式,即在线设施服务租赁问题(OFSL)。在OFSL中,租用不同(保健)设施地点的服务的期限和费用各不相同。每个设施的每项服务都与休眠费相关联,该费用需要在设施不租用服务的每一天支付。随着时间的推移,客户机到达,每个客户机请求许多服务,并且需要通过将它们连接到联合提供所请求服务的多个设施来提供服务。其目的是决定租赁哪些服务、何时以及租赁多长时间,以便在客户出现时尽快为所有客户提供服务,并将租赁、连接和休眠费用的成本降至最低。在本文中,我们研究了OFSL的推广,其中我们额外给出了一个参数d,这样,如果服务不连续租用超过d天,则需要支付休眠费(在OFSL的情况下d = 0)。我们将这种变体称为带有特定期限休眠费的在线设施服务租赁(d-OFSL)。我们特别关注问题的度量版本,其中设施和客户驻留在度量空间中。我们将其称为度量d-OFSL,并为该问题设计了第一个在线算法。后者是一种基于原始对偶方法的确定性算法。我们通过将其与所有问题实例的最优离线解决方案进行比较来衡量其性能。这种性能分析被称为竞争分析,是评估在线算法的标准。版权所有©2021由sciitepress -科学技术出版社,Lda。版权所有
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