Extent: | Online-Ressource (XI, 213p. 62 illus, digital) |
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Series: | |
Type of publication: | Book / Working Paper |
Type of publication (narrower categories): | Aufsatzsammlung |
Language: | English |
Notes: | Includes bibliographical references New State of MCDMin the 21st Century; Preface; Contents; Contributors; Part I MCDM Foundation and Theory; Chapter 1: MCDM: In Search of New Paradigms . . .; 1.1 MCDM: Its Roots and Early Beginnings; 1.2 Basic Definitions; 1.3 Systems Design of Optimality; 1.4 Tradeoffs-Free Management; Chapter 2: Harmonizing the Omnipresence of MCDM in Technology, Society, and Policy; 2.1 Historical Perspectives; 2.1.1 MCDM as a Philosophy That Inspired the Development of Theory, Methodology, and Practice of the Art and Science of Decision Making; 2.2 Ten Guiding Principles for the Practice of MCDM 2.2.1 First Principle: MCDM as a Harmonizing Discipline in Science, Technology, Society, and Policy Must Be Holistic2.2.2 Second Principle: A Common Denominator Bridges Risk Analysis and MCDM; 2.2.3 Third Principle: Models and State Variables Are Central to MCDM; 2.2.4 Fourth Principle: MCDM Must Account for Risk of Low Probability with Extreme Consequences; 2.2.5 Fifth Principle: MCDM Must Account for Knowledge Uncertainty and Variability Uncertainty; 2.2.6 Sixth Principle: MCDM Must Account for Emergent Forced Changes 2.2.7 Seventh Principle: Multiple Models Are Required to Represent the Multiple Perspectives of a System2.2.8 Eighth Principle: The Imperativeness of Selecting Representative Objectives and the Time Domain in MCDM; 2.2.9 Ninth Principle: The MCDM Process Must Be Holistic, Adaptive, Incremental, and Sustainable; 2.2.9.1 Why Holistic?; 2.2.9.2 Why Adaptive and Incremental?; 2.2.9.3 Why Sustainable?; 2.2.10 Tenth Principle: Phantom System Models Are Required for the Effective Practice of MCDM, While Building on and Adhering to All Nine Principles; 2.3 Epilogue; References Chapter 3: Decision Making on Pareto Front Approximations with Inherent Nondominance3.1 Introduction; 3.2 Notation and Definitions; 3.3 Inherent Nondominance and Inherently Nondominated Approximation of the PF; 3.4 Decision Making on the Approximation; 3.5 Conclusion; References; Chpater 4: A New Consistency Index for Comparison Matrices in the ANP; 4.1 Introduction; 4.2 Analysis of the Consistency Ratio Method and the Issues of Inconsistency Test in the ANP; 4.2.1 Analysis of the Consistency Ratio Method; 4.2.2 The Issues of Inconsistency Test in the ANP 4.3 The New Consistency Index for the ANP4.3.1 The Maximum Eigenvalue Threshold as the Consistency Index for the ANP; 4.3.2 The Analysis and Comparison; 4.3.3 The Block Diagonal Matrix and Judgment Process; 4.4 Illustrative Example; 4.5 Conclusions; References; Part II MCDM Methodology; Chapter 5: Estimating the Robustness of Composite CBA and MCA Assessments by Variation of Criteria Importance Order; 5.1 Introduction; 5.2 Case Study: Public Transport System; 5.2.1 Composite Assessment; 5.2.2 Decision Conference; 5.2.3 Robustness of the Composite Assessment; 5.3 Conclusion and Perspectives References |
ISBN: | 978-3-642-19695-9 ; 978-3-642-19694-2 |
Other identifiers: | 10.1007/978-3-642-19695-9 [DOI] |
Classification: | Methoden und Techniken der Betriebswirtschaft ; Numerische Mathematik ; Variationsrechnung ; Programmiermethodik |
Source: | ECONIS - Online Catalogue of the ZBW |
Persistent link: https://www.econbiz.de/10014015367