Models and Methods for Management Science

Description

This textbook introduces systems science as an entry point to present a basic introduction to research models and methods in management science (operation research). This textbook selects the classic quantitative models and methods as well as rich cases and detailed examples, which are suitable for students with a certain management and economics knowledge for further study, and helps to develop the abilities of using the basic models in real life. Preface Contents About the Editor 1 System Science 1.1 Formation and Development of System Science 1.1.1 The Development Process of System Science 1.1.2 The Main Schools of System Science 1.1.3 Development of System Science in China 1.2 Definition and Characteristics of System 1.2.1 Definition of System 1.2.2 Characteristics of System 1.3 Classification of System Further Readings 2 Decision-Making Methods 2.1 Overview of Decision-Making 2.1.1 Definition of Decision-Making 2.1.2 Classification of Decisions 2.1.3 Decision-Making Process 2.1.4 Basic Elements of the Decision-Making System 2.2 Certainty Decision-Making 2.3 Risk Decision-Making 2.3.1 Expected Value Analysis 2.3.2 Decision Tree Analysis 2.3.3 Bayesian Decision-Making 2.4 Uncertainty Decision-Making 2.4.1 Optimistic Law 2.4.2 Wald Law 2.4.3 Hurwicz Law 2.4.4 Laplace Law 2.4.5 Savage Law 2.5 Multi-Attribute Decision-Making 2.5.1 TOPSIS Method 2.5.2 VIKOR Law Further Readings 3 Prediction Methods 3.1 Overview of Prediction 3.1.1 The Meaning of Prediction 3.1.2 Classification of Predictions 3.1.3 Prediction Steps 3.2 Qualitative Prediction Methods 3.3 Quantitative Prediction Methods 3.3.1 Time Series Prediction 3.3.2 Regression Analysis Prediction Method 3.3.3 Trend Extrapolation Further Readings 4 Evaluation Methods 4.1 Overview of Evaluation Methods 4.1.1 Definition of Evaluation 4.1.2 Classification of Evaluation Methods 4.1.3 Evaluation Procedure 4.2 DEA (Data Envelopment Analysis) 4.2.1 Definition of DEA 4.2.2 DEA Analysis Model 4.2.3 Example 4.3 AHP (Analytic Hierarchy Process) 4.3.1 Principle of AHP 4.3.2 Example of AHP 4.3.3 Analytic Network Hierarchy Process 4.4 Fuzzy Comprehensive Evaluation 4.4.1 Definition of Fuzzy Comprehensive Evaluation 4.4.2 Fuzzy Mapping and Fuzzy Transformation 4.4.3 Steps of the Fuzzy Comprehensive Evaluation Method 4.4.4 Example of Fuzzy Comprehensive Evaluation 4.5 Entropy Evaluation 4.5.1 Fundamental Principle 4.5.2 Application Case 4.6 Set Pair Analysis 4.6.1 Fundamental Principle 4.6.2 Application Case Further Readings 5 Optimization Algorithm 5.1 Overview of Optimization Algorithm 5.1.1 Basic Concepts of Optimization Algorithms 5.1.2 Development of Intelligent Optimization Algorithms 5.2 PSO (Particle Swarm Optimization) 5.2.1 Algorithm Principle 5.2.2 Algorithm Model 5.2.3 Algorithm Flow 5.2.4 Parameter Analysis and Setting 5.2.5 Case Analysis 5.2.6 Advantages and Disadvantages of the Algorithm 5.2.7 Improvement of Particle Swarm Algorithm 5.3 GA (Genetic Algorithm) 5.3.1 Overview of Genetic Algorithm 5.3.2 The Basic Process of Genetic Algorithm 5.3.3 The Realization of Genetic Algorithm in MATLAB 5.4 FOA (Fruit Fly Optimization Algorithm) 5.4.1 Algorithm Principle and Model 5.4.2 Algorithm Evaluation and Improvement 5.5 WOA (Whale Optimization Algorithm) 5.5.1 Algorithm Principle and Implementation 5.5.2 Algorithm Evaluation and Improvement 5.6 GWO (Grey Wolf Optimization) 5.6.1 Algorithm Principle and Model 5.6.2 Algorithm Flow Further Readings 6 System Reliability 6.1 Overview of Reliability 6.1.1 Basic Concepts 6.1.2 Reliability Research Principle and Contents 6.1.3 Significance of Reliability Research 6.2 Reliability Eigenvector 6.3 System Reliability and Calculation 6.4 System Reliability Fault Analysis 6.4.1 Fault Tree Analysis 6.4.2 Bayesian Network 6.5 Application Case Summary Further Readings 7 Game Theory 7.1 Overview of Game Theory 7.1.1 Related Concepts of Game Theory 7.1.2 The Development of Game Theory 7.1.3 Game Theory and the Nobel Prize in Economics 7.2 Non-cooperative Game 7.2.1 Complete Information Game 7.2.2 Incomplete Information Game 7.3 Cooperative Game 7.3.1 Basic Concept 7.3.2 Distribution of Cooperative Games 7.3.3 Matching Game 7.4 Evolutionary Game 7.4.1 Overview 7.4.2 Evolutionary Stability Strategy (ESS) 7.4.3 Replicator Dynamic Further Readings 8 Management Simulation 8.1 Overview of Simulation 8.1.1 Concept of Simulation 8.1.2 Classification of Simulation 8.1.3 Role of Simulation 8.1.4 Modern Modeling and Simulation Technology 8.1.5 Common Techniques for Management Simulation 8.2 System Dynamics 8.2.1 What is System Dynamics? 8.2.2 Development and Prospect of System Dynamics 8.2.3 System Dynamics Application Steps 8.2.4 Basic Concept of System Dynamics 8.2.5 Testing of the Model 8.3 Multi-agent System 8.3.1 Overview of Multi-agent System 8.3.2 Multi-agent Modeling 8.3.3 AnyLogic-Based Multi-agent Models Further Readings 9 Complexity Science 9.1 Overview of Complexity Science 9.1.1 The Evolution of Complexity Science 9.1.2 Characteristics of Complex Systems 9.1.3 Dissipative Structure 9.1.4 Synergetics Theory 9.2 Chaos Theory 9.2.1 The Development of Chaotic Dynamics 9.2.2 Definition of Chaos 9.2.3 Characteristics of Chaos 9.2.4 Lyapunov Exponent 9.2.5 Logistic Map and Tent Map 9.2.6 Chaos Prediction 9.3 Catastrophe Theory 9.3.1 Theory Introduction 9.3.2 Fundamental Contents 9.3.3 The Mathematical Description of Catastrophe Theory 9.3.4 Catastrophe Progression Method 9.3.5 Theoretical Meaning 9.4 Hypercycle Theory 9.4.1 Theory Introduction 9.4.2 Theoretical Principle 9.4.3 Hierarchical Levels 9.4.4 Important Nature 9.4.5 Theoretical Significance 9.4.6 Fractal Theory 9.4.7 Theory Introduction 9.4.8 Definition 9.4.9 Fractal Dimension Measurement Method 9.4.10 Application of Fractal Theory 9.5 Self-organized Criticality Appendix Further Readings 10 Structural Equation Modeling 10.1 Overview of Structural Equation Modeling 10.2 Composition of Structural Equation Modeling 10.3 Application Case of Structural Equation Modeling Further Readings 11 Markov Chain 11.1 Markov Process 11.2 Markov Chain 11.2.1 Definition 11.2.2 Relevant Concepts 11.3 Classification of Markov Chain Models 11.3.1 Continuous-Time Markov Chains 11.3.2 Hidden Markov Model 11.4 Application of Markov Chain Models Further Readings 12 Grey Systems Theory 12.1 Basic Concepts of Grey Systems 12.2 Grey Correlation Analysis 12.2.1 Definition of Correlation Coefficient 12.2.2 An Example of Grey Correlation Analysis 12.3 Gm (1,1) 12.4 Grey Prediction Model 12.4.1 Definition of Grey Prediction 12.4.2 An Example of Grey Prediction Appendix Further Readings