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

Created from the Publication Database of the Vienna University of Technology.