Hybrid Heuristics for Multimodal Homecare Scheduling

Andrea Rendl (Vortragende:r), Matthias Prandtstetter, Gerhard Hiermann, Jakob Puchinger, G. Raidl

Publikation: Beitrag in Buch oder TagungsbandVortrag mit Beitrag in TagungsbandBegutachtung

Abstract

Abstract. We focus on hybrid solution methods for a large-scale realworld multimodal homecare scheduling (MHS) problem, where the objective is to nd an optimal roster for nurses who travel in tours from patient to patient, using di erent modes of transport. In a rst 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 nding promising solutions for large real-world MHS problem instances.
OriginalspracheEnglisch
TitelIntegration of AI and OR Techniques in Constraint Programming for Combinatorial Optimization Problems, Proceedings.
Redakteure/-innenNicolas Beldiceanu, Narendra Jussien, Eric Pinson
Herausgeber (Verlag)Springer
Seiten339-355
Seitenumfang17
PublikationsstatusVeröffentlicht - 2012
VeranstaltungThe 9th International Conference on the Integration of Artificial Intelligence and Operations Research into Constraint Programming (CPAIOR) -
Dauer: 28 Mai 20121 Juni 2012

Konferenz

KonferenzThe 9th International Conference on the Integration of Artificial Intelligence and Operations Research into Constraint Programming (CPAIOR)
Zeitraum28/05/121/06/12

Research Field

  • Ehemaliges Research Field - Mobility Systems

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