Using a genetic algorithm to solve a non-linear location allocation problem for specialised children's ambulances in England and Wales.

IF 1.2 Q4 HEALTH POLICY & SERVICES Health Systems Pub Date : 2021-04-18 eCollection Date: 2022-01-01 DOI:10.1080/20476965.2021.1908176
Enoch Kung, Sarah E Seaton, Padmanabhan Ramnarayan, Christina Pagel
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引用次数: 5

Abstract

Since 1997, special paediatric intensive care retrieval teams (PICRTs) based in 11 locations across England and Wales have been used to transport sick children from district general hospitals to one of 24 paediatric intensive care units. We develop a location allocation optimisation framework to help inform decisions on the optimal number of locations for each PICRT, where those locations should be, which local hospital each location serves and how many teams should station each location. Our framework allows for stochastic journey times, differential weights for each journey leg and incorporates queuing theory by considering the time spent waiting for a PICRT to become available. We examine the average waiting time and the average time to bedside under different number of operational PICRT stations, different number of teams per station and different levels of demand. We show that consolidating the teams into fewer stations for higher availability leads to better performance.

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利用遗传算法解决了英格兰和威尔士儿童救护车的非线性位置分配问题。
自1997年以来,设在英格兰和威尔士11个地点的儿科特别重症监护检索队(PICRTs)被用来将患病儿童从地区综合医院运送到24个儿科重症监护病房中的一个。我们开发了一个地点分配优化框架,以帮助决定每个PICRT的最佳地点数量,这些地点应该在哪里,每个地点为哪家当地医院服务,以及每个地点应该驻扎多少个团队。我们的框架允许随机行程时间,每个行程段的不同权重,并通过考虑等待PICRT可用的时间来结合排队理论。我们研究了在不同数量的PICRT站点、每个站点不同数量的团队和不同需求水平下的平均等待时间和平均到床边时间。我们展示了将团队整合到更少的站点以获得更高的可用性,从而获得更好的性能。
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来源期刊
Health Systems
Health Systems HEALTH POLICY & SERVICES-
CiteScore
4.20
自引率
11.10%
发文量
20
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