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Combinatorial Online Optimization: Elevators & Yellow Angels

Please always quote using this URN: urn:nbn:de:0297-zib-10360
  • In \emph{classical optimization} it is assumed that full information about the problem to be solved is given. This, in particular, includes that all data are at hand. The real world may not be so nice'' to optimizers. Some problem constraints may not be known, the data may be corrupted, or some data may not be available at the moments when decisions have to be made. The last issue is the subject of \emph{online optimization} which will be addressed here. We explain some theory that has been developed to cope with such situations and provide examples from practice where unavailable information is not the result of bad data handling but an inevitable phenomenon.

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Author:Martin Grötschel, Benjamin HillerORCiD, Andreas Tuchscherer
Document Type:ZIB-Report
Tag:Aufzugssteuerung; Dispatching von Fahrzeugen; Online-Optimierung
elevator control; online optimization; vehicle dispatching
MSC-Classification:68-XX COMPUTER SCIENCE (For papers involving machine computations and programs in a specific mathematical area, see Section -04 in that area) / 68Wxx Algorithms (For numerical algorithms, see 65-XX; for combinatorics and graph theory, see 05C85, 68Rxx) / 68W01 General
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C10 Integer programming
90-XX OPERATIONS RESEARCH, MATHEMATICAL PROGRAMMING / 90Cxx Mathematical programming [See also 49Mxx, 65Kxx] / 90C27 Combinatorial optimization
Date of first Publication:2007/11/19
Series (Serial Number):ZIB-Report (07-36)
Published in:Appeared under the title "Structuring a Dynamic Environment: Combinatorial Online Optimization of Logistics Processes" in: Emergence, Analysis and Evolution of Structures : Concepts and Strategies Across Disciplines. Klaus Lucas, Peter Roosen eds. Springer 2010, pp. 199-214
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