It is quite an onerous task to edit the proceedings of a two week long institute with learned contributors from many parts of the world. All the same, the editorial team has found the process of refereeing and reviewing the contributions worthwhile and completing the volume has proven to be a satisfying task. In setting up the institute we had considered models and methods taken from a number of different disciplines. As a result the whole institute - preparing for it, attending it and editing the proceedings - proved to be an intense learning experience for us. Here I speak on behalf of the committee and the editorial team. By the time the institute took place, the papers were delivered and the delegates exchanged their views, the structure of the topics covered and their relative positioning appeared in a different light. In editing the volume I felt compelled to introduce a new structure in grouping the papers. The contents of this volume are organised in eight main sections set out below: 1 . Abstracts. 2. Review Paper. 3. Models with Multiple Criteria and Single or Multiple Decision Makers. 4. Use of Optimisation Models as Decision Support Tools. 5. Role of Information Systems in Decision Making: Database and Model Management Issues. 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based Systems. 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems. 8. Mathematical Basis for Constructing Models and Model Validation.

Klappentext

This volume is based on the lectures presented by well-known experts at the NATO Advanced Study Institute on Mathematical Models for Decision Support held in Val d'Isère, France, July 26 - August 6, 1987. At the beginning the abstracts appear in a section of their own. This is followed by an extensive review paper which provides an overview of the major modeling issues in decision making. Thus, by first reading these two sections the readers may gain a fair glimpse of the contents of the remaining six sections of the volume. Researchers and practitioners interested in current Decision Support Systems issues and the directions in progress are the intended audience of this book. There is a particular emphasis on the adaptation of Artificial Intelligence techniques for use in decision making. Readers of this volume will find its structure and contents valuable and germane to their own field of study and research.

Inhalt

1. Abstracts.- Abstracts.- 2. Review Paper.- Models for Decision Making: An Overview of Problems, Tools and Major Issues.- 3. Models with Multiple Criteria and Single or Multiple Decision Makers.- Numerical Scaling of Human Judgement in Pairwise-Comparison Methods for Fuzzy Multi-Criteria Decision Analysis.- Some Mathematical Topics in the Analytic Hierarchy Process.- What is the Analytic Hierarchy Process?.- An Interactive DSS for Multiobjective Investment Planning.- Multiple Criteria Mathematical Programming: An Updated Overview and Several Approaches.- 4. Use of Optimisation Models as Decision Support Tools.- Language Requirements for a Priori Error Checking and Model Reduction in Large-Scale Programming.- A Note on the Reformulation of LP Models.- Interfaces Between Modeling Systems and Solution Algorithms.- Mathematical Programming Solutions for Fishery Management.- A General Network Generator.- A Case Study in the Use of Mathematical Models for Decision Support in Production Planning.- ANALYZE Rulebase.- Interfacing Optimizers with Planning Languages and Process Simulators.- A Multicriterial Decision Problem Within the Simplex Algorithm.- Interactive Distribution Planning.- Mathematical Programming on Microcomputers: Directions in Performance and User Interface.- Aggregation Models in Mathematical Programming.- Interactive Decision Support for Semi-Structured Mathematical Programming Problems.- 5. Role of Information Systems in Decision Making: Database and Model Management Issues.- Relational Data Management and Modeling Systems: A Tutorial.- Model Management Systems for Operations Research: A Prospectus.- Structured Model Management.- Choice Theory and Data Base.- 6. Methods of Artificial Intelligence in Decision Making: Intelligent Knowledge Based System.- A Financial Expert Decision Support System.- A Knowledge-Based System for Production Control of Flexible Manufacturing Systems.- A Knowledgebase for Formulating Linear Programs.- A Knowledge-Based System for Integrated Solving Cutting Stock Problems and Production Control in the Paper Industry.- Expert Systems: The State of the Art.- Automated Support for Formulating Linear Programs.- The Environment Approach to Decision Support.- 7. Representation of Uncertainty in Mathematical Models and Knowledge Based Systems.- Expert Systems' Front End: Expert Opinion.- Fuzzy Set Theoretic Approaches to Natural Language in Decision Support Systems.- Stochastic Programming Models for Dedicated Portfolio Selection.- Probabilistic and Non-Probabilistic Representation of Uncertainties in Expert Systems.- Panel Discussion on Representation of Uncertainty and Imprecision in Decision Support Systems.- 8. Mathematical Basis for Constructing Models and Model Validation.- Validation of Decision Support Systems.- Panel Discussion on DSS Validation.- DSS Conceptualizers in O.R: Should you apply AI?.- Fundamentals of Structured Modeling.- Mathematical Basis for Decision Support Systems.- Fuzzy Set Theory And Inference Mechanism.- 9. Summary of Software Products.- 10. List of Participants.