@unpublished{choetal16,
	abstract = {Ambulance redeployment refers to the practice of strategically relocating ambulances in real time to better respond to future call arrivals. Optimal redeployment policies can be found, in theory, via stochastic dynamic programming, but this approach succumbs to the curse of dimensionality. We instead consider the problem of finding an upper bound on the performance of optimal redeployment policies, which can be used, for instance, as a benchmark against which heuristic policies can be compared. Such a bound has been developed for systems in which calls can queue when no ambulances are available. We adapt this bound to loss systems, corresponding to the fairly common situation in which arriving calls are redirected to an alternative service if they cannot be immediately served. This adaptation is nontrivial, and involves the introduction of new ideas, including an integer program whose feasible region contains the set of decisions made by any member of a fairly general class of redeployment policies. We prove the validity of our upper bound, and study its performance through computational experiments.},
	author = {K. C. Chong and S. G. Henderson and M. E. Lewis and H. Topaloglu},
	date-added = {2016-01-10 17:38:59 +0000},
	date-modified = {2016-01-10 17:40:25 +0000},
	note = {Submitted},
	title = {A bound on the performance of optimal ambulance redeployment policies in loss systems},
	year = {2016}}

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