Please use this identifier to cite or link to this item: http://hdl.handle.net/10397/94140
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Title: A fleet deployment model to minimise the covering time of maritime rescue missions
Authors: Chen, X
Yan, R
Wu, S 
Liu, Z
Mo, H
Wang, S 
Issue Date: 2023
Source: Maritime policy and management, 2023, v. 50, no, 6, p. 724-749
Abstract: This paper investigates a covering time minimisation problem of the maritime rescue missions that arise in practical rescue operations in the context of Hong Kong waters. In this problem, a fleet of heterogeneous vessels is deployed at marine police bases to deal with emergencies. Once an emergency rescue request is received, the marine police should send sufficient vessels to arrive at the incident site as soon as possible to provide critical medical service to the injured or the sick. A basic question to the rescue missions is that what is the minimal covering time that marine police could promise to arrive at any incident site. The shorter time the water district can be covered, the more likely lives and properties can be saved and the better the rescue service is. To address this problem, this paper formulates a mixed-integer programming model. Considering the expensive computational cost, a two-stage method is proposed. Extensive numerical experiments and a case study are performed to demonstrate the efficiency of the proposed algorithm and illustrate how our model can be applied to solve practical problems. Our study contributes to the stream of research on maritime rescue problem that is gaining increasing concern in recent years.
Keywords: Fleet deployment
Maritime rescue
Minimal covering time
Mixed-integer programming problem
Publisher: Routledge, Taylor & Francis Group
Journal: Maritime policy and management 
ISSN: 0308-8839
EISSN: 1464-5254
DOI: 10.1080/03088839.2021.2017042
Rights: © 2022 Informa UK Limited, trading as Taylor & Francis Group
This is an Accepted Manuscript of an article published by Taylor & Francis in Maritime policy and management on 31 Dec 2021 (Published online), available online: http://www.tandfonline.com/10.1080/03088839.2021.2017042.
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