NDLI: A new probabilistic coverage model for ambulances deployment with hypercube queuing approach

Content Provider	Springer Nature Link
Author	Davoudpour, H. Mortaz, E. Hosseinijou, S. A.
Copyright Year	2013
Abstract	Aiming at improving the efficiency and reliability of ambulance service, several location models for ambulance stations have been proposed in the facility location literature. Two well-known approaches to this problem are coverage and median models. Coverage model looks for the location to maximize the (deterministic or probabilistic) covered demand of ambulance calls. Hence, this model can be thought of reliability-oriented model. In median model, the objective is to minimize the total traveling distance of the ambulances from the station to the scene of call and thus is the cost-oriented model. In this paper, a new probabilistic coverage model is introduced. It uses the idea of MEXCLP and mixes it with the hypercube queuing model. The model is applied in a real case for one of Tehran city's zones in Iran. The results were satisfactory and show the applicability of the model. Sensitivity analysis was conducted to determine the overall behavior of system responsiveness against parameters of the model. Discussions on sensitivity analysis are presented.
Starting Page	1157
Ending Page	1168
Page Count	12
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	70
Issue Number	5-8
e-ISSN	14333015
Language	English
Publisher	Springer London
Publisher Date	2013-10-17
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	Emergency service vehicles MEXCLP Hypercube queuing model Ambulance deployment Industrial and Production Engineering Production/Logistics/Supply Chain Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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