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  • 1
    Online-Ressource
    Online-Ressource
    Modeling with Stochastic Programming / (2024)
    Cham :Springer International Publishing :
    Details
    UID:
    almafu_9961535668902883
    Umfang: 1 online resource (213 pages)
    Ausgabe: 2nd ed. 2024.
    ISBN: 9783031545504 , 3031545508
    Serie: Springer Series in Operations Research and Financial Engineering,
    Inhalt: This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental modeling issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway.
    Anmerkung: Uncertainty in Optimization -- Information Structures and Feasibility -- Modeling the Objective Function -- Scenario Tree Generation, With Michal Kaut and Jamie Fairbrother -- High-Dimentional Dependent Randomness. With Zhaoxia Guo and Michal Kaut -- Service Network Design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic -- A Multi-dimensional Newsboy Problem with Substitution, With Hajnalka Vaagen -- References -- Index.
    Weitere Ausg.: ISBN 9783031545498
    Weitere Ausg.: ISBN 3031545494
    Sprache: Englisch
    Fachgebiete: Wirtschaftswissenschaften
    RVK:
    QH 237
    DOI: 10.1007/978-3-031-54550-4
    URL: Volltext  (URL des Erstveröffentlichers)
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    Online Zugang
    Open Access Wunsch
    HTW Berlin
    Charité
    BTU Cottbus
  • 2
    Online-Ressource
    Online-Ressource
    Modeling with Stochastic Programming / (2024)
    Cham, Switzerland :Springer,
    Details
    UID:
    edoccha_9961535668902883
    Umfang: 1 online resource (213 pages)
    Ausgabe: Second edition.
    ISBN: 3-031-54550-8
    Serie: Springer Series in Operations Research and Financial Engineering Series
    Inhalt: This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental modeling issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway.
    Anmerkung: Uncertainty in Optimization -- Information Structures and Feasibility -- Modeling the Objective Function -- Scenario Tree Generation, With Michal Kaut and Jamie Fairbrother -- High-Dimentional Dependent Randomness. With Zhaoxia Guo and Michal Kaut -- Service Network Design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic -- A Multi-dimensional Newsboy Problem with Substitution, With Hajnalka Vaagen -- References -- Index.
    Weitere Ausg.: ISBN 3-031-54549-4
    Sprache: Englisch
    DOI: 10.1007/978-3-031-54550-4
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    Open Access Wunsch
    Charité
  • 3
    Online-Ressource
    Online-Ressource
    Modeling with Stochastic Programming (2024)
    Cham : Springer
    Details
    UID:
    gbv_1890577243
    Umfang: 1 Online-Ressource (XVIII, 202 p. 34 illus., 15 illus. in color.)
    Ausgabe: 2nd ed.
    ISBN: 9783031545504
    Serie: Springer Series in Operations Research and Financial Engineering
    Inhalt: Uncertainty in Optimization -- Information Structures and Feasibility -- Modeling the Objective Function -- Scenario Tree Generation, With Michal Kaut and Jamie Fairbrother -- High-Dimentional Dependent Randomness. With Zhaoxia Guo and Michal Kaut -- Service Network Design, With Arnt-Gunnar Lium and Teodor Gabriel Crainic -- A Multi-dimensional Newsboy Problem with Substitution, With Hajnalka Vaagen -- References -- Index.
    Inhalt: This is an updated version of what is still the only text to address basic questions about how to model uncertainty in mathematical programming, including how to reformulate a deterministic model so that it can be analyzed in a stochastic setting. This second edition has important extensions regarding how to represent random phenomena in the models (also called scenario generation) as well as a new chapter on multi-stage models. This text would be suitable as a stand-alone or supplement for a second course in OR/MS or in optimization-oriented engineering disciplines where the instructor wants to explain where models come from and what the fundamental modeling issues are. The book is easy-to-read, highly illustrated with lots of examples and discussions. It will be suitable for graduate students and researchers working in operations research, mathematics, engineering and related departments where there is interest in learning how to model uncertainty. Alan King is a Research Staff Member at IBM's Thomas J. Watson Research Center in New York. Stein W. Wallace is a Professor of Operational Research and head of Center for Shipping and Logistics at NHH Norwegian School of Economics, Bergen, Norway.
    Weitere Ausg.: ISBN 9783031545498
    Weitere Ausg.: ISBN 9783031545511
    Weitere Ausg.: ISBN 9783031545528
    Weitere Ausg.: Erscheint auch als Druck-Ausgabe King, Alan J. Modeling with stochastic programming Cham : Springer, 2024 ISBN 9783031545498
    Weitere Ausg.: ISBN 9783031545511
    Weitere Ausg.: ISBN 9783031545528
    Sprache: Englisch
    DOI: 10.1007/978-3-031-54550-4
    URL: lizenzpflichtig
    URL: Cover
    Bibliothek Standort Signatur Band/Heft/Jahr Verfügbarkeit
    BibTip Andere fanden auch interessant ...
    Online-Ressource
    Open Access Wunsch
    UB Potsdam
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