Fuzzy Quantitative Management: Principles, Methodologies and Applications (Fuzzy Management Methods)

✍ Scribed by Shaopei Lin, Guohua Zhao

• Publisher: Springer
• Year: 2023
• Tongue: English
• Leaves: 179
• Category: Library

✦ Synopsis

This book is devoted to fuzzy quantitative studies in managerial science, discussing the philosophical background and decision-making essentials. For reference, a series of practical examples illustrate broad areas of application that are important in project risk management problems, and in complicated mega projects. Using computers to simulate human intelligence with fuzzy approaches is the basis of “Fuzzy-AI model,” which offers an efficient tool capable of simulating human intelligence in order to perform digitized decision inference and quantitative information management.

✦ Table of Contents

Foreword
Preface
Contents
About the Authors
1 Philosophical Consideration of Quantitative Management
1.1 Background Information of Quantitative Management
1.2 Philosophical Background of Managerial Science
1.3 Philosophical Considerations of “System-Fuzzy” Model
1.4 Philosophical Considerations of “Quantitative Management”
1.5 Conclusive Remarks
References
2 “Fuzz-AI Model” for Quantitative Management
2.1 The Features of Quantitative Management
2.2 What So-Called “Fuzzy-AI Model”?
2.3 Theoretical Foundation
2.3.1 The Meaningfulness of Fuzzy-AI Model
2.3.2 Setting of “Fuzzy-AI Model”
2.3.3 Fuzzy Distance with Variation Weights
2.3.4 Fuzzy Distance by Nearness Degree
2.4 Decision of Long-Term Highway Maintenance Investment
2.4.1 The Introducing of Pavement Damage State Indicator, PDSI
2.4.2 Fuzzy Model for the Decision of Highway Maintenance Investment
2.4.3 Elliptic Damage Model for Highway Maintenance Investment
2.4.4 Fuzzy Investment Decision Maintenance Investment of Highway System
2.5 Conclusive Remarks
References
3 The Conceptual Investigation of “Deep Data” and “Deep Knowledge”
3.1 “Deep Data/Knowledge” in a Decision System
3.2 Representation of Hierarchical Space of State
3.3 Fuzzy Deep Knowledge Reasoning Approach
3.3.1 Mathematical Distance in Space
3.3.2 Fuzzy Hierarchy Reasoning Approach
3.3.3 Weight Distribution Between Attributes
3.3.4 Illustrative Example
3.3.5 Fuzzy Decision Making
3.4 Fuzzy Decision in Bidding
3.4.1 Problem Illustration
3.4.2 Mathematical Modeling
3.4.3 Solving Procedures
3.4.4 Case Studies
3.5 Conclusive Remarks
References
4 Fuzzy Quantitative Risk Management
4.1 Background in Fuzzy Quantitative Risk Management
4.2 Project Risk in the Reality
4.3 Risk Knowledge Framework (RKF)
4.3.1 Hierarchical Structure of RKF
4.3.2 Functions of RKF
4.4 Software Architecture of Knowledge Based Fuzzy Decision Supporting System (KB-FDSS)
4.4.1 Expression of Risk Through Fuzzy Set
4.4.2 Fuzzy Assessment and Quantification of Risks
4.4.3 System Function of KB-FDSS
4.5 Example Verification of Risk Evaluation
4.6 Establishment of the Knowledge Base for Fuzzy Decision-Making of Risks
4.7 Conclusive Remarks
References
5 Quantitative Risk Decision of Overseas Projects
5.1 Project Risks in Overseas Engineering Market
5.2 Modeling of the Problem
5.2.1 The Contents and Characteristics of Project Investment Risk
5.2.2 The Indicator System of Economic Risks in Project Investment
5.3 Soft Strength and Human Error Risk in Overseas Projects
5.3.1 Risk Control and “Soft Strength” of Enterprises
5.3.2 Human Factor Induced Decision Error in Overseas Project Risk Management
5.3.3 Factors and Traps of Wrong Decision
5.3.4 Psychological Analysis of Decision Trap
5.4 Case Studies
5.4.1 Real Estate Project Investment Risks in New York City
5.4.2 High-Speed Railway Investment Risks
5.5 Conclusive Remarks
References
6 System Dynamics Modeling and Applied to International PPP Project Risk Evaluation
6.1 Development Characteristics of System Dynamics
6.2 System Analysis of Overseas PPP Project Risks
6.2.1 The Concept and Characteristics of System Science
6.2.2 The Capacity Expected by System Methodology
6.2.3 Elements of System Component
6.2.4 The System Risks of Overseas PPP Projects
6.2.5 Case Study of System Dynamics Modeling of Project Financing Risk
6.2.6 The Implementation of Risk Management Overseas of PPP Project
6.2.7 System Analysis and Action of Risk for Overseas PPP Projects
6.3 Risk Control and System Dynamics Model of Overseas PPP Project
6.3.1 The Advantages of System Dynamics Model
6.3.2 The Establishment of System Dynamics Model
6.3.3 Soft Risk Analysis of Overseas PPP Project
6.4 Solution of Soft System Dynamics Model for Overseas PPP Projects
6.4.1 Six Kinds of Soft Risks in Overseas PPP Project
6.4.2 Solution of FAHP Method
6.4.3 Building Risk Factor Framework in FAHP System Dynamics Model Solution
6.4.4 Weight Order of Sub-Risk (Attributes) Determined by Eigen-Value Solution
6.4.5 Case Study
6.4.6 Practical Treatment of Overseas PPP Project
6.5 Conclusive Remarks
References
7 Fuzzy TOPSIS Method for the Cost Prediction in Bridge Engineering Project
7.1 Background Information
7.2 On Fuzzy TOPSIS Method
7.3 Bridge Cost Prediction Review
7.3.1 Investigational Review in the Prediction of Engineering Cost
7.3.2 Sample Matching Ideas
7.3.3 Fuzzy Method
7.3.4 Conclusion
7.4 Method Selection of Cost Prediction
7.4.1 Indicators of Engineering Cost Prediction
7.4.2 Fuzzy Method
7.4.3 Fuzzy TOPSIS Method
7.5 Case Study
7.5.1 Data Treatment
7.5.2 Calculation Results
7.5.3 Sensitivity Analysis
7.6 Conclusive Remarks
References
8 The Advantages of Quantitative Management in Decision
8.1 Two Kinds of Events with Different Nature and Its Modeling
8.2 Theoretical Basis and Application Areas of “Fuzzy-AI Model”
8.3 Some Modeling Expressions of Quantitative Management
8.3.1 MP (Mathematical Programming) Model
8.3.2 NM (Nearness and Matching) Model
8.3.3 Max/Min Indicator Model
8.3.4 AE (Assessment and Evaluation) Model
8.4 Quantitative Management Perspectives
8.5 Conclusive Remarks
References
9 On Fuzzy Method of “Deep Knowledge” and “Deep Data” in Project Quantitative Management
9.1 The Background Information
9.2 Representative Expression of Hierarchical Space of State
9.2.1 Multi-Layered Hierarchy Space
9.2.2 Mathematical Distance in Space
9.3 Fuzzy Hierarchy Reasoning Approach
9.3.1 Space Chart Analysis
9.3.2 Fuzzy State Assessment
9.3.3 Weight Distribution Between Attributes
9.4 Illustrative Example
9.4.1 Space Chart of Event
9.4.2 Fuzzy Decision Making
9.5 Fuzzy Decision in Bidding
9.5.1 Mathematical Modeling
9.5.2 Solving Procedures
9.6 Case Studies
9.7 Conclusive Remarks
References
10 Perspectives in Combining Fuzzy and AI Techniques in Quantitative Management
10.1 Background Information
10.1.1 Facing Digitization of Project Management
10.1.2 Case Guide
10.1.3 What Should We Understand?
10.2 Two Types of Economy and Its Characteristics
10.3 Business Mode Under “Internet” Era and Knowledge Economy
10.4 Sustainable Development of Successful Enterprise Under Knowledge Economy
10.5 Case Study—E-commerce and Logistics
10.6 Program of Studies on Project Management Under Digital Era and Knowledge Economy
10.7 Case Studies—Expert System for Airplane Structural Design
10.7.1 On AI and Expert System for Structural Design
10.7.2 Production System and Inference Network
10.7.3 The Building of Expert System for Airplane Structural Design
10.8 Internet + AI Based Engineering Application Systems
10.8.1 Background Information
10.8.2 The AI Exploration for Application Systems
10.9 PMO Under Internet Era
10.10 Summary
10.11 Conclusive Remarks
References