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Hybrid Heuristics for Multimodal Homecare Scheduling

Abstract : We focus on hybrid solution methods for a large-scale real-world 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.
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https://hal.inria.fr/hal-01307979
Contributor : Jakob Puchinger <>
Submitted on : Wednesday, April 27, 2016 - 9:34:55 AM
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Andrea Rendl, Matthias Prandtstetter, Gerhard Hiermann, Jakob Puchinger, Günther Raidl. Hybrid Heuristics for Multimodal Homecare Scheduling. CPAIOR 2012: International Conference on Integration of Artificial Intelligence and Operations Research Techniques in Constraint Programming, May 2012, Nantes, France. pp.Pages 339-355, ⟨10.1007/978-3-642-29828-8_22⟩. ⟨hal-01307979⟩

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