Facility location under service level constraints for heterogeneous customers
Abstract
We study the problem of locating service facilities to serve heterogeneous customers. Customers requiring service are classified as either high priority or low priority, where
high priority customers are always served on a priority basis. The problem is to optimally
locate service facilities and allocate their service zones to satisfy the following coverage
and service level constraints: (1) each demand zone is served by a service facility within a
given coverage radius; (2) at least αh proportion of the high priority customers at any service
facility should be served without waiting; (3) at least αl proportion of the low priority cases
at any service facility should not have to wait for more than τl minutes. For this, we model
the network of service facilities as spatially distributed priority queues, whose locations and
user allocations need to be determined. The resulting integer programming problem is challenging to solve, especially in absence of any known analytical expression for the service
level function of low priority customers. We develop a cutting plane based solution algorithm, exploiting the concavity of the service level function of low priority customers to
outer-approximate its non-linearity using supporting planes, determined numerically using
matrix geometric method. Using an illustrative example of locating emerging medical service
facilities in Austin, Texas, we present computational results and managerial insights
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