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Interactive Fuzzy Optimization

  • Book
  • © 1991

Overview

Editors:
  1. Mario Fedrizzi

    1. Institute of Computer Science, University of Trento, Trento, Italy

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  2. Janusz Kacprzyk

    1. Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

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    You can also search for this editor in PubMed   Google Scholar

  3. Marc Roubens

    1. Institute of Mathematics, University of Liège, Liège, Belgium

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Part of the book series: Lecture Notes in Economics and Mathematical Systems (LNE, volume 368)

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Table of contents (19 chapters)

  1. Front Matter

    Pages I-VII
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  2. Introductory Sections

    1. Front Matter

      Pages 1-1
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    2. Fuzzy Set Theory and Modelling of Natural Language Semantics

      • Vilém Novák
      Pages 2-14

    3. A Survey of Fuzzy Optimization and Mathematical Programming

      • Mario Fedrizzi, Janusz Kacprzyk, José L. Verdegay
      Pages 15-28

  3. Fuzzy Optimization: General Issues and Related Topics

    1. Front Matter

      Pages 29-29
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    2. Minimizing a Fuzzy Function

      • Elio Canestrelli, Silvio Giove
      Pages 30-35

    3. A Concept of Optimality for Fuzzified Mathematical Programming Problems

      • Margit Kovács
      Pages 36-44

    4. Some Properties of Possibilistic Linear Equality Systems with Weakly Noninteractive Fuzzy Numbers

      • Robert Fullér
      Pages 45-48

    5. Fuzzy Preferences in Linear Programming

      • Jaroslav Ramík
      Pages 49-58

    6. Implication Relations, Equivalence Relations and Hierarchical Structure of Attributes in Multiple Criteria Decision Making

      • Jochen Ester
      Pages 59-70

    7. Uncertain Multiobjective Programming as a Game Against Nature

      • J. J. Buckley
      Pages 71-77

    8. Approaching Fuzzy Integer Linear Programming Problems

      • F. Herrera, J. L. Verdegay
      Pages 78-91

    9. Interactive Bicriteria Integer Programming: A Performance Analysis

      • R. Ramesh, M. H. Karwan, S. Zionts
      Pages 92-100

    10. Interactive Approaches for Solving some Decision Making Problems in the Czechoslovak Power Industry

      • Martin Černý, Dagmar Glückaufová
      Pages 101-110

  4. Issues Related to Interactive Decision Making

    1. Front Matter

      Pages 111-111
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    2. Elicitation of Opinions by Means of Possibilistic Sequences of Questions

      • Bernadette Bouchon-Meunier
      Pages 112-119

    3. Searching Fuzzy Concepts in a Natural Language Data Base

      • A. F. Rocha, M. Theoto
      Pages 120-125

    4. Reconfigurable Network Architecture for Distributed Problem Solving

      • Jacek Maitan, Zbigniew W. Ras
      Pages 126-137

  5. Algorithms and Software for Interactive Fuzzy Optimization

    1. Front Matter

      Pages 139-139
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    2. Interactive Decision Making for Multiobjective Linear Programming Problems with Fuzzy Parameters Based on a Solution Concept Incorporating Fuzzy Goals

      • Masatoshi Sakawa, Hitoshi Yano
      Pages 140-153
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Keywords

About this book

The title of this book seems to indicate that the volume is dedicated to a very specialized and narrow area, i. e. , to the relationship between a very special type of optimization and mathematical programming. The contrary is however true. Optimization is certainly a very old and classical area which is of high concern to many disciplines. Engineering as well as management, politics as well as medicine, artificial intelligence as well as operations research, and many other fields are in one way or another concerned with optimization of designs, decisions, structures, procedures, or information processes. It is therefore not surprising that optimization has not grown in a homogeneous way in one discipline either. Traditionally, there was a distinct difference between optimization in engineering, optimization in management, and optimization as it was treated in mathematical sciences. However, for the last decades all these fields have to an increasing degree interacted and contributed to the area of optimization or decision making. In some respects, new disciplines such as artificial intelligence, descriptive decision theory, or modern operations research have facilitated, or even made possible the interaction between the different classical disciplines because they provided bridges and links between areas which had been developing and applied quite independently before. The development of optimiiation over the last decades can best be appreciated when looking at the traditional model of optimization. For a well-structured, Le.

Editors and Affiliations

  • Institute of Computer Science, University of Trento, Trento, Italy

    Mario Fedrizzi

  • Systems Research Institute, Polish Academy of Sciences, Warsaw, Poland

    Janusz Kacprzyk

  • Institute of Mathematics, University of Liège, Liège, Belgium

    Marc Roubens

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