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A. Rendl, M. Prandtstetter, G. Hiermann, J. Puchinger, G. Raidl:
"A hybrid heuristic for multimodal homecare scheduling";
Talk: International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming, Nantes, Frankreich; 2012-05-28 - 2012-06-01; in: "Integration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems", volume 7298 of LNCS (2012), ISBN: 978-3-642-29827-1; 339 - 355.

We focus on hybrid solution methods for a large-scale realworld
multimodal homecare scheduling (MHS) problem, where the objective
is to find an optimal roster for nurses who travel in tours from patient
to patient, using different modes of transport. In a first step, we generate
a valid initial solution using Constraint Programming (CP). In a second
step, we improve the solution using one of the following metaheuristic
approaches: (1) variable neighborhood descent, (2) variable neighborhood
search, (3) an evolutionary algorithm, (4) scatter search and (5) a
simulated annealing hyper heuristic. Our evaluation, based on computational
experiments, demonstrates how hybrid approaches are particularly
strong in finding promising solutions for large real-world MHS problem
instances.

http://publik.tuwien.ac.at/files/PubDat_213381.pdf