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  • 1
    Online Resource
    Online Resource
    TOPSIS and its Extensions: A Distance-Based MCDM Approach (2022)
    Cham :Springer International Publishing :
    Details
    UID:
    almahu_9949372171402882
    Format: XV, 221 p. 15 illus., 14 illus. in color. , online resource.
    Edition: 1st ed. 2022.
    ISBN: 9783031095771
    Series Statement: Studies in Systems, Decision and Control, 447
    Content: The objective of the book is to provide materials to demonstrate the development of TOPSIS and to serve as a handbook. It contains the basic process of TOPSIS, numerous variant processes, property explanations, theoretical developments, and illustrative examples with real-world cases. Possible readers would be graduate students, researchers, analysts, and professionals who are interested in TOPSIS, a distance-based algorithm, and who would like to compare TOPSIS with other MCDM methods. The book serves as a research reference as well as a self-learning book with step-by-step illustrations for the MCDM community.
    Note: Multiple Criteria Modeling -- TOPSIS for Decision Support -- TOPSIS Applications -- Index.
    In: Springer Nature eBook
    Additional Edition: Printed edition: ISBN 9783031095764
    Additional Edition: Printed edition: ISBN 9783031095788
    Additional Edition: Printed edition: ISBN 9783031095795
    Language: English
    Subjects: Economics
    RVK:
    QH 424
    DOI: 10.1007/978-3-031-09577-1
    URL: https://doi.org/10.1007/978-3-031-09577-1
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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    HU Berlin
    TH Brandenburg
    HTW Berlin
    BTU Cottbus
  • 2
    Online Resource
    Online Resource
    Fuzzy and multi-level decision making : soft computing approaches (2019)
    Cham : Springer
    Details
    UID:
    b3kat_BV045389321
    Format: 1 Online-Ressource (xi, 219 Seiten , Illustrationen, Diagramme
    Edition: Second edition
    ISBN: 9783319925257
    Series Statement: Studies in fuzziness and soft computing 368
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-92524-0
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 978-3-319-92526-4
    Language: English
    Subjects: Mathematics
    RVK:
    SK 830
    Keywords: Fuzzy-Logik
    DOI: 10.1007/978-3-319-92525-7
    URL: Volltext  (URL des Erstveröffentlichers)
    Author information: Shih, Hsu-shih 1955-
    Author information: Lee, E. Stanley 1930-
    Library Location Call Number Volume/Issue/Year Availability
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    Online Access
    Open Access Request
    TH Brandenburg
    HTW Berlin
    BTU Cottbus
  • 3
    Online Resource
    Online Resource
    TOPSIS and its extensions : a distance-based MCDM approach (2022)
    Cham, Switzerland :Springer,
    Details
    UID:
    almafu_9960862237602883
    Format: 1 online resource (230 pages)
    ISBN: 3-031-09577-4
    Series Statement: Studies in Systems, Decision and Control ; v.447
    Note: Intro -- 498715_1_En_BookFrontmatter_OnlinePDF -- Preface -- Objective of the Study -- Book Organization -- Acknowledgements -- Contents -- About the Authors -- List of Figures -- 498715_1_En_1_Chapter_OnlinePDF -- 1 Multiple Criteria Modeling -- 1.1 Problems -- 1.2 Problem-Solving Process -- 1.3 Multiple Criteria Formulation -- 1.4 Alternatives -- 1.5 Solutions -- 1.6 Validation and Verification -- 1.7 Summary and Discussions -- References -- 498715_1_En_2_Chapter_OnlinePDF -- 2 TOPSIS Basics -- 2.1 Origin, Benefits, and Drawbacks -- 2.2 TOPSIS Algorithm -- 2.3 TOPSIS Choice Behavior -- 2.4 TOPSIS Inputs -- 2.5 Current Developments -- 2.6 Illustrative Example: A Recruitment and Selection Problem -- 2.7 Summary and Discussions -- References -- 498715_1_En_3_Chapter_OnlinePDF -- 3 TOPSIS Variants -- 3.1 Normalization Process -- 3.2 Weights for Aggregation -- 3.3 Distance Functions -- 3.4 Selection on PIS/NIS -- 3.5 Relative Closeness Formula -- 3.6 Ordinal Input -- 3.7 Weights on Separation Measures -- 3.8 Dependent Criteria -- 3.8.1 ANP Concept -- 3.8.2 Mahalanobis Distance -- 3.8.3 Other Approaches -- 3.9 Incremental Analysis -- 3.10 Summary and Discussions -- References -- 498715_1_En_4_Chapter_OnlinePDF -- 4 Group Aspects of TOPSIS -- 4.1 Backgrounds of Group Decisions -- 4.2 Group Decision Processes -- 4.3 Consensus in Group TOPSIS -- 4.3.1 Consensus Measures and Reaching -- 4.3.2 Consensus Reaching Process -- 4.3.3 Ngwenyama et al.'s Approach -- 4.3.4 Madu's Approach -- 4.4 Consensus on Thresholds -- 4.5 Summary and Discussions -- Appendix A -- References -- 498715_1_En_5_Chapter_OnlinePDF -- 5 TOPSIS for Decision Support -- 5.1 Necessity of Decision Support -- 5.2 DSS Configurations and Components -- 5.2.1 DSSs and GDSSs -- 5.2.2 TOPSIS's Components -- 5.3 TOPSIS-Supported DSS Applications -- 5.3.1 Manufacturing Location Selection GDSS. , 5.3.2 Product Development DSS -- 5.3.3 Recruitment and Selection GDSS -- 5.3.4 Investment Evaluation DSS -- 5.3.5 Green Product Design DSS -- 5.3.6 Closed-Loop Supply Chain Network Design DSS -- 5.3.7 Customer-Driven Product Design DSS -- 5.3.8 Manufacturing System Reconfiguration DSS -- 5.3.9 Food Supply Chains DSS -- 5.3.10 Safety Inspection DSS -- 5.3.11 Automobile Components Procurement DSS -- 5.4 Summary and Discussions -- References -- 498715_1_En_6_Chapter_OnlinePDF -- 6 Sorting Problems by TOPSIS -- 6.1 TOPSIS for Sorting -- 6.2 Proposed Sorting Approach -- 6.2.1 Determination of Cut-Off Values -- 6.2.2 Suggested Sorting Procedure -- 6.3 Analytic Results -- 6.3.1 Case Background -- 6.3.2 Comparative Results -- 6.4 Summary and Discussions -- References -- 498715_1_En_7_Chapter_OnlinePDF -- 7 Rank Reversal in TOPSIS -- 7.1 Rank Reversal -- 7.2 TOPSIS Rank Reversal -- 7.3 Illustrative Examples -- 7.4 Theoretical Insights -- 7.5 Summary and Discussions -- References -- 498715_1_En_8_Chapter_OnlinePDF -- 8 Other Related Methods -- 8.1 Fuzzy TOPSIS -- 8.1.1 Fuzzy Numbers -- 8.1.2 Fuzzy Operations -- 8.1.3 Fuzzy TOPSIS Approach -- 8.1.4 Choquet Integral for TOPSIS -- 8.2 VIKOR -- 8.3 BWM -- 8.4 Summary and Discussions -- References -- 498715_1_En_9_Chapter_OnlinePDF -- 9 TOPSIS Applications -- 9.1 Selection Applications -- 9.1.1 Location Decisions -- 9.1.2 Selection Decisions -- 9.1.3 Other Applications -- 9.2 Assessment Applications -- 9.3 Group Applications -- 9.3.1 Effectiveness -- 9.4 Conclusions -- References -- 498715_1_En_BookBackmatter_OnlinePDF -- Index.
    Additional Edition: Print version: Shih, Hsu-Shih TOPSIS and Its Extensions: a Distance-Based MCDM Approach Cham : Springer International Publishing AG,c2022 ISBN 9783031095764
    Language: English
    Subjects: Economics
    RVK:
    QH 424
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    HWR Berlin
    Charité
  • 4
    Online Resource
    Online Resource
    Fuzzy and Multi-Level Decision Making : An Interactive Computational Approach (2001)
    London : Springer London
    Details
    UID:
    b3kat_BV045148756
    Format: 1 Online-Ressource (IX, 193 p)
    ISBN: 9781447106838
    Series Statement: Advanced Manufacturing
    Content: Managerial Decisions in hierarchy organizations, such as the various manufacturing and service companies, are difficult to formalize and even more difficult to optimize. By exploring the typical fuzziness, vagueness, or the "not-well-defined" nature of such organizations, this book presents the first comprehensive treatment of this difficult and practically important problem. The advantages of the proposed fuzzy interactive approach are that it significantly reduces computational requirements. Equally, the representation of the system is made more realistic through the recognition of the inherent fuzziness of such large organizations. Both the multi-ploy and the game-like decision making processes, also known as multi-level programming and the fuzzy interactive approach, are discussed in detail. The emphasis is on numerical algorithms and numerous examples are solved and compared. The concepts of fuzzy set and fuzzy linguistic representation, which form an integral part of any managerial decision, are also discussed
    Additional Edition: Erscheint auch als Druck-Ausgabe ISBN 9781447111771
    Language: English
    Keywords: Entscheidungsfindung ; Mehrebenenoptimierung ; Fuzzy-Logik
    DOI: 10.1007/978-1-4471-0683-8
    URL: Volltext  (URL des Erstveröffentlichers)
    Library Location Call Number Volume/Issue/Year Availability
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    BTU Cottbus
  • 5
    Book
    Book
    Fuzzy and multi-level decision making : an interactive computational approach (2001)
    London [u.a.] : Springer-Verlag
    Details
    UID:
    kobvindex_ZLB12493825
    Format: IX, 193 Seiten , graph. Darst. , 24 cm
    Edition: 1
    ISBN: 1852331577
    Series Statement: Advanced manufacturing
    Note: Literaturverz. S. 177 - 187 , Text engl.
    Language: English
    Keywords: Entscheidungsprozess ; Interaktive Optimierung ; Fuzzy-Logik
    Library Location Call Number Volume/Issue/Year Availability
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    Book
    Berlin VÖBB/ZLB get availability status
  • 6
    Online Resource
    Online Resource
    Fuzzy and Multi-Level Decision Making: Soft Computing Approaches / (2019)
    Cham :Springer International Publishing :
    Details
    UID:
    edoccha_9959767643302883
    Format: 1 online resource (XI, 219 p. 29 illus., 8 illus. in color.)
    Edition: 2nd ed. 2019.
    ISBN: 3-319-92525-3
    Series Statement: Studies in Fuzziness and Soft Computing, 368
    Content: This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
    Note: Introduction -- Linear Bi-level Programming -- Possibility Theory and Fuzzy Optimization -- Fuzzy Interactive Multi-level Decision Making -- Aggregation of Fuzzy Systems in Multi-level Decisions -- Multi-level Optimization by Fuzzy Dynamic Programming -- Auction Mechanisms for Solving Multi-level Programming -- Neural Networks for Solving Multi-level Programming -- Metaheuristics for Multi-level Optimization.
    Additional Edition: ISBN 3-319-92524-5
    Language: English
    DOI: 10.1007/978-3-319-92525-7
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Charité
  • 7
    Online Resource
    Online Resource
    TOPSIS and its extensions : a distance-based MCDM approach (2022)
    Cham, Switzerland :Springer,
    Details
    UID:
    edoccha_9960862237602883
    Format: 1 online resource (230 pages)
    ISBN: 3-031-09577-4
    Series Statement: Studies in Systems, Decision and Control ; v.447
    Note: Intro -- 498715_1_En_BookFrontmatter_OnlinePDF -- Preface -- Objective of the Study -- Book Organization -- Acknowledgements -- Contents -- About the Authors -- List of Figures -- 498715_1_En_1_Chapter_OnlinePDF -- 1 Multiple Criteria Modeling -- 1.1 Problems -- 1.2 Problem-Solving Process -- 1.3 Multiple Criteria Formulation -- 1.4 Alternatives -- 1.5 Solutions -- 1.6 Validation and Verification -- 1.7 Summary and Discussions -- References -- 498715_1_En_2_Chapter_OnlinePDF -- 2 TOPSIS Basics -- 2.1 Origin, Benefits, and Drawbacks -- 2.2 TOPSIS Algorithm -- 2.3 TOPSIS Choice Behavior -- 2.4 TOPSIS Inputs -- 2.5 Current Developments -- 2.6 Illustrative Example: A Recruitment and Selection Problem -- 2.7 Summary and Discussions -- References -- 498715_1_En_3_Chapter_OnlinePDF -- 3 TOPSIS Variants -- 3.1 Normalization Process -- 3.2 Weights for Aggregation -- 3.3 Distance Functions -- 3.4 Selection on PIS/NIS -- 3.5 Relative Closeness Formula -- 3.6 Ordinal Input -- 3.7 Weights on Separation Measures -- 3.8 Dependent Criteria -- 3.8.1 ANP Concept -- 3.8.2 Mahalanobis Distance -- 3.8.3 Other Approaches -- 3.9 Incremental Analysis -- 3.10 Summary and Discussions -- References -- 498715_1_En_4_Chapter_OnlinePDF -- 4 Group Aspects of TOPSIS -- 4.1 Backgrounds of Group Decisions -- 4.2 Group Decision Processes -- 4.3 Consensus in Group TOPSIS -- 4.3.1 Consensus Measures and Reaching -- 4.3.2 Consensus Reaching Process -- 4.3.3 Ngwenyama et al.'s Approach -- 4.3.4 Madu's Approach -- 4.4 Consensus on Thresholds -- 4.5 Summary and Discussions -- Appendix A -- References -- 498715_1_En_5_Chapter_OnlinePDF -- 5 TOPSIS for Decision Support -- 5.1 Necessity of Decision Support -- 5.2 DSS Configurations and Components -- 5.2.1 DSSs and GDSSs -- 5.2.2 TOPSIS's Components -- 5.3 TOPSIS-Supported DSS Applications -- 5.3.1 Manufacturing Location Selection GDSS. , 5.3.2 Product Development DSS -- 5.3.3 Recruitment and Selection GDSS -- 5.3.4 Investment Evaluation DSS -- 5.3.5 Green Product Design DSS -- 5.3.6 Closed-Loop Supply Chain Network Design DSS -- 5.3.7 Customer-Driven Product Design DSS -- 5.3.8 Manufacturing System Reconfiguration DSS -- 5.3.9 Food Supply Chains DSS -- 5.3.10 Safety Inspection DSS -- 5.3.11 Automobile Components Procurement DSS -- 5.4 Summary and Discussions -- References -- 498715_1_En_6_Chapter_OnlinePDF -- 6 Sorting Problems by TOPSIS -- 6.1 TOPSIS for Sorting -- 6.2 Proposed Sorting Approach -- 6.2.1 Determination of Cut-Off Values -- 6.2.2 Suggested Sorting Procedure -- 6.3 Analytic Results -- 6.3.1 Case Background -- 6.3.2 Comparative Results -- 6.4 Summary and Discussions -- References -- 498715_1_En_7_Chapter_OnlinePDF -- 7 Rank Reversal in TOPSIS -- 7.1 Rank Reversal -- 7.2 TOPSIS Rank Reversal -- 7.3 Illustrative Examples -- 7.4 Theoretical Insights -- 7.5 Summary and Discussions -- References -- 498715_1_En_8_Chapter_OnlinePDF -- 8 Other Related Methods -- 8.1 Fuzzy TOPSIS -- 8.1.1 Fuzzy Numbers -- 8.1.2 Fuzzy Operations -- 8.1.3 Fuzzy TOPSIS Approach -- 8.1.4 Choquet Integral for TOPSIS -- 8.2 VIKOR -- 8.3 BWM -- 8.4 Summary and Discussions -- References -- 498715_1_En_9_Chapter_OnlinePDF -- 9 TOPSIS Applications -- 9.1 Selection Applications -- 9.1.1 Location Decisions -- 9.1.2 Selection Decisions -- 9.1.3 Other Applications -- 9.2 Assessment Applications -- 9.3 Group Applications -- 9.3.1 Effectiveness -- 9.4 Conclusions -- References -- 498715_1_En_BookBackmatter_OnlinePDF -- Index.
    Additional Edition: Print version: Shih, Hsu-Shih TOPSIS and Its Extensions: a Distance-Based MCDM Approach Cham : Springer International Publishing AG,c2022 ISBN 9783031095764
    Language: English
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Charité
  • 8
    Online Resource
    Online Resource
    Fuzzy and Multi-Level Decision Making: Soft Computing Approaches / (2019)
    Cham :Springer International Publishing :
    Details
    UID:
    almafu_9959767643302883
    Format: 1 online resource (XI, 219 p. 29 illus., 8 illus. in color.)
    Edition: 2nd ed. 2019.
    ISBN: 3-319-92525-3
    Series Statement: Studies in Fuzziness and Soft Computing, 368
    Content: This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
    Note: Introduction -- Linear Bi-level Programming -- Possibility Theory and Fuzzy Optimization -- Fuzzy Interactive Multi-level Decision Making -- Aggregation of Fuzzy Systems in Multi-level Decisions -- Multi-level Optimization by Fuzzy Dynamic Programming -- Auction Mechanisms for Solving Multi-level Programming -- Neural Networks for Solving Multi-level Programming -- Metaheuristics for Multi-level Optimization.
    Additional Edition: ISBN 3-319-92524-5
    Language: English
    DOI: 10.1007/978-3-319-92525-7
    Library Location Call Number Volume/Issue/Year Availability
    BibTip Others were also interested in ...
    Online Resource
    Open Access Request
    Charité
  • 9
    Book
    Book
    Fuzzy and multi-level decision making : an interactive computational approach (2001)
    London : Springer
    Details
    UID:
    gbv_266172326
    Format: IX, 193 S , graph. Darst , 24 cm
    ISBN: 1852331577
    Series Statement: Advanced manufacturing series
    Note: Includes bibliographical references and index
    Language: English
    Subjects: Mathematics
    RVK:
    SK 830
    Keywords: Entscheidungsprozess ; Interaktive Optimierung ; Fuzzy-Logik ; Entscheidungsfindung ; Fuzzifizierung ; Mehrebenenoptimierung
    URL: Cover
    URL: Inhaltsverzeichnis
    Author information: Lee, E. Stanley 1930-
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    Stabi Berlin get availability status
  • 10
    Online Resource
    Online Resource
    Fuzzy and Multi-Level Decision Making: Soft Computing Approaches (2019)
    Cham :Springer International Publishing :
    Details
    UID:
    almahu_9948030300402882
    Format: XI, 219 p. 29 illus., 8 illus. in color. , online resource.
    Edition: 2nd ed. 2019.
    ISBN: 9783319925257
    Series Statement: Studies in Fuzziness and Soft Computing, 368
    Content: This book offers a comprehensive overview of cutting-edge approaches for decision-making in hierarchical organizations. It presents soft-computing-based techniques, including fuzzy sets, neural networks, genetic algorithms and particle swarm optimization, and shows how these approaches can be effectively used to deal with problems typical of this kind of organization. After introducing the main classical approaches applied to multiple-level programming, the book describes a set of soft-computing techniques, demonstrating their advantages in providing more efficient solutions to hierarchical decision-making problems compared to the classical methods. Based on the book Fuzzy and Multi-Level Decision Making (Springer, 2001) by Lee E.S and Shih, H., this second edition has been expanded to include the most recent findings and methods and a broader spectrum of soft computing approaches. All the algorithms are presented in detail, together with a wealth of practical examples and solutions to real-world problems, providing students, researchers and professionals with a timely, practice-oriented reference guide to the area of interactive fuzzy decision making, multi-level programming and hierarchical optimization.
    Note: Introduction -- Linear Bi-level Programming -- Possibility Theory and Fuzzy Optimization -- Fuzzy Interactive Multi-level Decision Making -- Aggregation of Fuzzy Systems in Multi-level Decisions -- Multi-level Optimization by Fuzzy Dynamic Programming -- Auction Mechanisms for Solving Multi-level Programming -- Neural Networks for Solving Multi-level Programming -- Metaheuristics for Multi-level Optimization.
    In: Springer eBooks
    Additional Edition: Printed edition: ISBN 9783319925240
    Additional Edition: Printed edition: ISBN 9783319925264
    Language: English
    DOI: 10.1007/978-3-319-92525-7
    URL: https://doi.org/10.1007/978-3-319-92525-7
    Library Location Call Number Volume/Issue/Year Availability
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    Online Resource
    Open Access Request
    HU Berlin
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