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A Bound on the Performance of an Optimal Ambulance Redeployment Policy

Matthew S. Maxwell (), Eric Cao Ni (), Chaoxu Tong (), Shane G. Henderson (), Huseyin Topaloglu () and Susan R. Hunter ()
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Matthew S. Maxwell: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Eric Cao Ni: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Chaoxu Tong: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Shane G. Henderson: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Huseyin Topaloglu: School of Operations Research and Information Engineering, Cornell University, Ithaca, New York 14853
Susan R. Hunter: School of Industrial Engineering, Purdue University, West Lafayette, Indiana 47907

Operations Research, 2014, vol. 62, issue 5, 1014-1027

Abstract: Ambulance redeployment is the practice of repositioning ambulance fleets in real time in an attempt to reduce response times to future calls. When redeployment decisions are based on real-time information on the status and location of ambulances, the process is called system-status management. An important performance measure is the long-run fraction of calls with response times over some time threshold. We construct a lower bound on this performance measure that holds for nearly any ambulance redeployment policy through comparison methods for queues. The computation of the bound involves solving a number of integer programs and then simulating a multiserver queue. This work originated when one of the authors was asked to analyze a response to a request-for-proposals (RFP) for ambulance services in a county in North America.

Keywords: system-status management; ambulance location; ambulance relocation; ambulance deployment; move-up; coupling (search for similar items in EconPapers)
Date: 2014
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Citations: View citations in EconPapers (15)

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