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Metaheuristics for solving a Multimodal Home-Health Care Scheduling Problem Gerhard Hiermann∗, Andrea Rendl†, Matthias Prandtstetter†, Jakob Puchinger†and G¨ unther Raidl‡ November 7, 2011
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Document Date: 2013-09-23 07:14:30


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City

Boston / Maidenhead / /

Company

McGraw-Hill Ltd. / Addison-Wesley Longman Publishing Co. Inc. / Verkehrsverbund Ost-Region GmbH / Sozial Global AG / /

Country

United States / United Kingdom / /

Currency

pence / /

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Facility

Vienna University of Technology / Austrian Institute of Technology / Vienna University of Technology E-Mail / University of Nottingham / /

IndustryTerm

local search algorithm / travel time estimations / parent solutions / feasible solution / e.g. travel time / good solutions / scatter search approach / hybrid evolutionary algorithm / local search / diverse solutions / worst solution / travel times / scatter search / mobile software / recombination operator / /

Organization

School of Computer Science / Operational Research Society / Austrian Federal Ministry for Transport / Innovation and Technology / Institute of Technology / Vienna / Vienna University of Technology E-Mail / University of Nottingham / Mobility Department / Vienna University of Technology / /

Person

Jingpeng Li / Graham Kendall / Andrea Rendl / Manuel Laguna / David E. Goldberg / Matthias Prandtstetter / Edmund K. Burke / Gerhard Hiermann / Pablo Moscato / Rong Qu / Fred Glover / Ruibin Bai / Jakob Puchinger / Rafael Mart / Barry Mccollum / Timothy Curtois / Jacek Blazewicz / /

Position

Each nurse / non-smoking nurse / specific nurse / nurse / swap-nurse / /

ProvinceOrState

Massachusetts / /

PublishedMedium

Machine Learning / IEEE Transactions on Evolutionary Computation / /

Technology

ghiermann@hotmail.com Algorithms / local search algorithm / Simulated Annealing algorithm / Memetic algorithm / artificial intelligence / Machine Learning / recombination / Memetic algorithms / hybrid evolutionary algorithm / be obtained using an hybrid evolutionary algorithm / /

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