Fuzzy and Multi-Level Decision Making: An Interactive Computational Approach

摘要: 1. Introduction.- 1.1 Decision Making in Hierarchy Systems: Multi-ploy versus Interactive Decisions.- 1.2 Bi-Level and Multi-level Programming.- 1.3 Characteristics of Duo-ploy Systems.- 1.4 Systems with Multi-followers.- 1.5 Fuzzy Making.- 2. Linear Bi-level 2.1 2.2 Extreme-point Search.- 2.2.1 kth-best Algorithm.- 2.2.2 Grid-search 2.3 Transformation Approach.- 2.3.1 Mixed-integer 2.3.2 Complementary-pivot algorithm.- 2.3.2.1 Parametric 2.3.2.2 Sequential Complementary Algorithm Branch-and-bound.- 2.3.3 Branch-and-bound 2.3.3.1 Bard Moore.- 2.3.3.2 Hansen et al.- 2.3.4 Penalty-function 2.4 Discussions.- 3. Other Programming Algorithms.- 3.1 Distributed 3.1.1 Problem Slackness.- 3.1.2 3.2 Three-level Problem.- 3.2.1 Hybrid Search 3.2.2 3.2.3 Simplex-cutting-plane 3.2.4 3.3 Non-linear 3.3.1 Linear-quadratic 3.3.2 Steepest-descent 3.3.3 Evolutionary Approach: Genetic 3.4 Discrete 3.5 4. Possibility Theory Knowledge Representation.- 4.1 Theory.- 4.1.1 Distribution.- 4.1.2 Measure.- 4.1.3 Measure Based on Set Subset.- 4.1.4 Probability.- 4.2 4.2.1 Linguistic Variable.- 4.2.2 The Syntactic Rule.- 4.2.3 Semantic 4.2.4 Test-score Semantics.- 5. 5.1 5.2 Multiple-objective 5.2.1 Compromise 5.2.2 Goal 5.3 Approach to 5.4 Parameters.- 5.5 5.5.1 5.5.2 6. 6.1 6.2 6.3 6.4 6.5 7. Aggregation 7.1 Compensation 7.2Compensation Multiple-level Problems.- 7.3 Decentralized Equally Important Objectives.- 7.4 Unequally 7.5 7.6 7.7 8. Possibilistic Minimum-cost Flow 8.1 8.2 8.2.1 Capacity Constraint Modification.- 8.2.2 8.3 Multi-objective 8.4 8.5 References.