Multiple Criteria Decision Analysis in Regional Planning

1 Introduction to Multiple Criteria Decision Making.- 1.1 Modern Society as a Problems Complex.- 1.2 General Characteristics of Modern Systems Analysis.- 1.2.1 Historical Background.- 1.2.2 Characteristics of Modern Systems Analysis.- 1.3 Characteristics of Multiple Criteria Decision Analysis.- 1.3.1 Objects to be Analyzed.- 1.3.2 General Description of Methodology.- 1.4 Outline of the Book.- 2 Approach to Multiple Criteria Optimization.- 2.1 Pareto Optimality.- 2.1.1 Multiple Criteria Optimization.- 2.1.2 Concept of Pareto Optimality.- 2.1.3 Economic Analysis and Pareto Optimality.- 2.2 Derivation of the Pareto Optimal Frontier.- 2.2.1 Scalarization.- 2.2.2 Kuhn-Tucker Theorems.- 2.2.3 Weighting Method.- 2.2.4 Lagrangian Constraint Method.- 2.2.5 ?-constraint Method.- 2.3 Selection of the Preferred Decisions.- 2.3.1 Search on the Pareto Optimal Frontier.- 2.3.2 Optimal Weights and Market Prices.- 2.3.3 Lagrange Multiplier and Imputed Price.- 2.3.4 Surrogate Worth Trade-off Method.- 3 Interactive Multiobjective Mathematical Programming.- 3.1 Goal Programming and Compromise Programming.- 3.1.1 Goal Programming.- 3.1.2 Compromise Programming.- 3.2 Interactive Frank-Wolfe Method and Its Variants.- 3.2.1 Interactive Frank-Wolfe Method.- 3.2.2 Proxy Method.- 3.2.3 Trade-off Cut Method.- 3.3 Sequential Proxy Optimization Technique (SPOT).- 3.3.1 Introduction.- 3.3.2 Methodological Description.- 3.4 Reference Point Method and Its Extensions.- 3.4.1 Reference Point Method.- 3.4.2 Reference Point Method with Trade-off Information.- 4 Interactive Fuzzy Multiobjective Programming.- 4.1 Introduction.- 4.1.1 Fundamentals of Fuzzy Set Theory.- 4.1.2 Problem Formulation.- 4.2 Interactive Fuzzy Multiobjective Programming without Trade-offs.- 4.2.1 Interactive Fuzzy Goal Programming.- 4.2.2 Interactive Fuzzy Penalty Scalarizing Method.- 4.3 Interactive Fuzzy Multiobjective Programming with Trade-offs.- 4.3.1 Interactive Fuzzy Constraint Method.- 4.3.2 Interactive Fuzzy Minimax Method.- 4.3.3 Interactive Fuzzy Augmented Minimax Method.- 4.4 Interactive Computer Program.- 4.4.1 Computer Package.- 4.4.2 Illustrative Example.- 5 The Preference Structure of Decision Making.- 5.1 Hypothesis of Rational Human Behavior.- 5.1.1 Introduction.- 5.1.2 Axioms for Rational Human Behavior.- 5.2 Expected Utility Hypothesis.- 5.2.1 Preference Relation and Preference Order.- 5.2.2 Existence of the Numerical Utility Function.- 5.2.3 Expected Utility Hypothesis.- 5.2.4 Digressions.- 5.3 The Generalized Nonlinear Utility Function and Risk Attitudes.- 5.4 Application to Technology Assessment for Substitute Energy.- 6 Multiattribute Utility Analysis.- 6.1 Representation Theorem of Multiattribute Utility Functions.- 6.2 Identification of the Single Attribute Utility Function.- 6.3 Identification of the Multiattribute Utility Function.- 6.3.1 Independence Check.- 6.3.2 Assessment of Scaling Constants.- 6.3.3 Checks for the Representation Forms and for Coherence of the Preference Order.- 6.4 Hierarchical Structuring of Preferences: Nesting.- 6.4.1 Decision Hierarchy.- 6.4.2 Nesting of Preferences.- 6.5 Interactive Computer Program for Subjective Systems.- 6.5.1 Discussion on Multiattribute Utility Analysis.- 6.5.2 Assistance by Computer Programs.- 6.5.3 Assessment of the Scaling Constants for MUF.- 6.5.4 The Computer Package: ICOPSS.- 6.5.5 Application to Prior Assessment for the Bullet Train Network.- 7 Value Conflicts in Multiple Agents Decision Making.- 7.1 Extension of Multiattribute Utility Analysis.- 7.2 Approaches to Collective Choice.- 7.2.1 Construction of Group Utility Functions.- 7.2.2 Treatment of the Diversified Evaluation.- 7.3 Probability Assessment and Entropy Model.- 7.3.1 Probability Assessment and Collective Choice.- 7.3.2 Entropy Model and Default Index: The Entropy Evaluation Method (EEM).- 7.3.3 Application to Regional Planning.- 7.4 Fuzzy Multiattribute Utility Analysis.- 7.4.1 Fuzzy Extension of Multiattribute Utility Analysis.- 7.4.2 Fuzzy Preference Ordering.- 7.4.3 Derivation of a Nonfuzzy Collective Preference Ordering.- 7.4.4 Construction of the Fuzzy Multiattribute Utility Function.- 7.5 Stochastic Dominance Rules for Collective Choice.- 8 Reconsideration of Preference Structure.- 8.1 Strength of Preference and Measurable Value Functions.- 8.1.1 Beyond the Concept of the Utility Function under Uncertainty.- 8.1.2 Concepts of the Value Function under Certainty.- 8.1.3 Aggregation Rule of the Measurable Value Function.- 8.2 The Measurable Value Function for Risky Choice.- 8.2.1 Measurable Value Function under Uncertainty.- 8.2.2 Gambles Embodied Preference Differences.- 8.2.3 Foundations of the Expected Value Function.- 8.2.4 Relative Risk Attitude.- 8.2.5 Extensions to Collective Choice.- 8.3 Partial Comparable Axioms without Transitivity.- 8.3.1 Value Function with Indifference Intransitiveness.- 8.3.2 Large Preference and Indistinctive Outranking.- 8.3.3 Application to Organizational Decision Making.- 9 Resource Allocation and Duality.- 9.1 Introduction.- 9.2 Economic Analysis and Equilibrium Prices.- 9.3 Shadow Market and Imputed Prices.- 9.3.1 Negative Utility and Shadow Prices.- 9.3.2 Derivation of the Negative Demand Function.- 9.3.3 Evaluation of the Negative Utility Goods.- 10 Imputation of Dual Prices.- 10.1 Introduction.- 10.2 Nonlinear Programming and Dual Prices.- 10.2.1 Duality of Convex Programming and Its Implication.- 10.2.2 Generalized MUltiobjective Nonlinear Programming and the Dual Prices.- 10.3 The Kuhn-Tucker MUltiplier as General Evaluation Factor.- 10.4 Nested Lagrangian Multiplier (NLM) Method.- 10.4.1 Introduction.- 10.4.2 MUltiobjective Interpretation of Mathematical Programming.- 10.4.3 The Kuhn-Tucker Multiplier as the Basic Evaluation Factor.- 10.4.4 Transformation of the Kuhn-Tucker MUltiplier to a Quasi-Utility Function and Its Nesting.- 10.4.5 Summary and Remarks.- 11 Applications of the Nested Lagrangian Multiplier (NLM) Method.- 11.1 The Nested Lagrangian Multiplier (NLM) Method in Application.- 11.2 MUltiobjective Evaluation of Regional Planning in the Greater Osaka Area: A Static Case.- 11.3 MUltiobjective Evaluation of Regional Planning in the Grea ter Osaka Area: A Dynamic Case.- 11.4 Industrial Land-use Program Combined with Water Quality Control: A Dynamic Case.- 12 Interpretation of Duality in Game Theory.- 12.1 Introduction.- 12.2 Noncooperative Games (Two-person Zerosum).- 12.3 N-Person Cooperative Games and Nucleolus.- 12.4 Example: Evaluation for Efficient Formation of Interregional Agreement.- 13 Propriety of Multiple Criteria Decision Making for Human Affairs: Social Implementation and Personal Behavior.- 13.1 Introduction.- 13.2 Properties and Functions of the Decision Maker.- 13.2.1 Agglomeration Process of Decision Making.- 13.2.2 Legitimacy of the Decision Maker.- 13.3 Hierarchical Structure of Human Needs.- 13.4 Cultural Domain in Decision Making.- 13.4.1 A Primitive Model.- 13.4.2 Interpretative Inquiry.- 13.5 Concluding Remarks.- References.- Bibliography on Multiple Criteria Decision Making (Books).- (Collective Papers).