Multicriteria Decision Making

1. Front Matter

   Pages i-xx

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2. Decision-Aiding Today: What Should We Expect?

   • Bernard Roy

   Pages 1-35

3. Theory of Vector Maximization: Various Concepts of Efficient Solutions

   • Johannes Jahn

   Pages 37-68

4. Duality in Multi-Objective Optimization

   • Hirotaka Nakayama

   Pages 69-97

5. Preference Relations and MCDM

   • Carlos A. Bana e Costa, Jean-Claude Vansnick

   Pages 99-121

6. Normative and Descriptive Aspects of Decision Making

   • Oleg I. Larichev

   Pages 123-146

7. Meta Decision Problems in Multiple Criteria Decision Making

   • Thomas Hanne

   Pages 147-171

8. Sensitivity Analysis in MCDM

   • Tetsuzo Tanino

   Pages 173-201

9. Goal Programming

   • Sang M. Lee, David L. Olson

   Pages 203-235

10. Reference Point Approaches

    • Andrzej P. Wierzbicki

    Pages 237-275

11. Concepts of Interactive Programming

    • Theodor J. Stewart

    Pages 277-304

12. Outranking Approach

    • Philippe Vincke

    Pages 305-333

13. Multi-Criteria Problem Structuring and Analysis in a Value Theory Framework

    • Valerie Belton

    Pages 335-366

14. Fundamentals of Interior Multiple Objective Linear Programming Algorithms

    • Ami Arbel

    Pages 367-396

15. The Use of Rough Sets and Fuzzy Sets in MCDM

    • Salvatore Greco, Benedetto Matarazzo, Roman Slowinski

    Pages 397-455

16. Use of Artificial Intelligence in MCDM

    • Patrice Perny, Jean-Charles Pomerol

    Pages 457-499

17. Evolutionary Algorithms and Simulated Annealing for MCDM

    • Andrew J. Chipperfield, James F. Whidborne, Peter J. Fleming

    Pages 501-532

18. Back Matter

    Pages 533-538

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At a practical level, mathematical programming under multiple objectives has emerged as a powerful tool to assist in the process of searching for decisions which best satisfy a multitude of conflicting objectives, and there are a number of distinct methodologies for multicriteria decision-making problems that exist. These methodologies can be categorized in a variety of ways, such as form of model (e.g. linear, non-linear, stochastic), characteristics of the decision space (e.g. finite or infinite), or solution process (e.g. prior specification of preferences or interactive). Scientists from a variety of disciplines (mathematics, economics and psychology) have contributed to the development of the field of Multicriteria Decision Making (MCDM) (or Multicriteria Decision Analysis (MCDA), Multiattribute Decision Making (MADM), Multiobjective Decision Making (MODM), etc.) over the past 30 years, helping to establish MCDM as an important part of management science. MCDM has become a central component of studies in management science, economics and industrial engineering in many universities worldwide.
Multicriteria Decision Making: Advances in MCDM Models, Algorithms, Theory and Applications aims to bring together `state-of-the-art' reviews and the most recent advances by leading experts on the fundamental theories, methodologies and applications of MCDM. This is aimed at graduate students and researchers in mathematics, economics, management and engineering, as well as at practicing management scientists who wish to better understand the principles of this new and fast developing field.

• algorithms
• calculus
• linear optimization
• multi-objective optimization
• optimization

`I highly recommend the book to a broad audience of graduate students and scientists in operations research, economics, management sciences, and engineering, and to practitioners interested in following recent developments in MCDM.'
Interfaces, 31:3(2001)

• Fern Universität, Hagen, Germany

  Tomas Gal, Thomas Hanne

• University of Cape Town, Rep. of South Africa

  Theodor J. Stewart

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