Optimal ambulance location with random delays and travel times
TLDR
An ambulance location optimization model that minimizes the number of ambulances needed to provide a specified service level and considers response time to be composed of a random delay (prior to travel to the scene) plus a random travel time is described.Abstract:
We describe an ambulance location optimization model that minimizes the number of ambulances needed to provide a specified service level. The model measures service level as the fraction of calls reached within a given time standard and considers response time to be composed of a random delay (prior to travel to the scene) plus a random travel time. In addition to modeling the uncertainty in the delay and in the travel time, we incorporate uncertainty in the ambulance availability in determining the response time. Models that do not account for the uncertainty in all three of these components may overestimate the possible service level for a given number of ambulances and underestimate the number of ambulances needed to provide a specified service level. By explicitly modeling the randomness in the ambulance availability and in the delays and the travel times, we arrive at a more realistic ambulance location model. Our model is tractable enough to be solved with general-purpose optimization solvers for cities with populations around one Million. We illustrate the use of the model using actual data from Edmonton.read more
Citations
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Journal ArticleDOI
Fundamentals of Queueing Theory
TL;DR: The Fundamentals of Queueing Theory, Fourth Edition as discussed by the authors provides a comprehensive overview of simple and more advanced queuing models, with a self-contained presentation of key concepts and formulae.
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Taxonomic classification of planning decisions in health care: a structured review of the state of the art in OR/MS
Peter J. H. Hulshof,Nikky Kortbeek,Nikky Kortbeek,Richard J. Boucherie,Erwin W. Hans,Piet J. M. Bakker +5 more
TL;DR: A comprehensive overview of the typical decisions to be made in resource capacity planning and control in health care, and a structured review of relevant articles from the field of Operations Research and Management Sciences (OR/MS) for each planning decision.
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Operations Research in Healthcare: a survey
TL;DR: This paper surveys several applications of Operations Research in the domain of Healthcare and highlights current research activities, focusing on a variety of optimisation problems as well as solution techniques used for solving the Optimisation problems.
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A survey of healthcare facility location
TL;DR: A framework to classify different types of non-emergency and emergency HCFs in terms of location management is presented, and the literature based on the framework is reviewed and future research possibilities are analyzed.
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Ambulance location for maximum survival
TL;DR: The survival-maximizing location models are better suited for EMS location than the covering models which do not adequately differentiate between consequences of different response times.
References
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Book
Fundamentals of queueing theory
TL;DR: The Fundamentals of Queueing Theory, Fourth Edition as discussed by the authors provides a comprehensive overview of simple and more advanced queuing models, with a self-contained presentation of key concepts and formulae.
Journal ArticleDOI
Fundamentals of Queueing Theory
TL;DR: The Fundamentals of Queueing Theory, Fourth Edition as discussed by the authors provides a comprehensive overview of simple and more advanced queuing models, with a self-contained presentation of key concepts and formulae.
Journal ArticleDOI
The maximal covering location problem
TL;DR: The use of a maximal service distance as a measure of the value of a given locational configuration has been discussed at length by Toregas and ReVelle 1 who show that it is an important surrogate measurement for the value.
Journal ArticleDOI
The location of emergency service facilities
TL;DR: In this paper, the location of emergency facilities is viewed as a set covering problem with equal costs in the objective, where sets are composed of the potential facility points within a specified time or