  Capital goods such as complex medical equipment, trains and manufacturing
machinery are essential to their users' business, and thus have stringent
up-time requirements. Responsive maintenance is crucial for meeting these
requirements, which in turn relies on the timely availability of both spare
parts and service engineers. Spare parts management for maintenance is
well-studied in the research literature, but managing the service engineers has
received relatively little attention. In this paper, we consider a network of
geographically distributed capital goods, maintained by a set of service
engineers who can respond quickly to machine breakdowns. We are interested in
the question which service engineers to dispatch to what breakdowns, and how to
relocate these engineers to maintain good coverage. We propose and evaluate a
range of scalable dispatching and relocation heuristics inspired by the
extensive research literature in the domain of emergency medical services. We
compare the proposed heuristics against each other using comprehensive
simulation experiments, and benchmark the best combination of dispatching and
relocation heuristics against the optimal policy. We find that this heuristic
performs close to optimal, while easily scaling to realistic-sized networks,
making it suitable for practical applications.
