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Multiobjective Optimization: Behavioral and Computational Considerations

  • Book
  • © 1992

Overview

Authors:
  1. Jeffrey L. Ringuest

    1. Operations Research and Strategic Management, Wallace Carroll School of Management, Boston College, Chestnut Hill, USA

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Table of contents (10 chapters)

  1. Front Matter

    Pages i-xv
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  2. Introduction

    • Jeffrey L. Ringuest
    Pages 1-17

  3. Linear Goal Programming

    • Jeffrey L. Ringuest
    Pages 19-37

  4. Generalizing Goal Programming

    • Jeffrey L. Ringuest
    Pages 39-50

  5. Compromise Programming

    • Jeffrey L. Ringuest
    Pages 51-59

  6. Decision Making and the Efficient Set

    • Jeffrey L. Ringuest
    Pages 61-80

  7. Interactive Methods

    • Jeffrey L. Ringuest
    Pages 81-94

  8. Computational Efficiency and Problems with Special Structure

    • Jeffrey L. Ringuest
    Pages 95-109

  9. Computational Efficiency and Linear Problems of General Structure

    • Jeffrey L. Ringuest
    Pages 111-143

  10. Using Multiobjective Linear Programming to Reconcile Preferences Over Time

    • Jeffrey L. Ringuest
    Pages 145-152

  11. Data Presentation and Multiobjecitve Optimization

    • Jeffrey L. Ringuest
    Pages 153-164

  12. Back Matter

    Pages 165-169
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Keywords

About this book

Throughout the development of mathematical programming researchers have paid great attention to problems that are described by a single objective that can only be achieved subject to satisfying a set of restrictions or constraints. Recently, it has been recognized that the use of a single objective limits the applicability of In reality, many multiobjective mathematical programming models. situations exist and frequently these mUltiple objectives are in direct conflict. Research on multiobjective problems can be broken down into two broad categories: multiobjective optimization and multicriterion decision theory. Multiobjective optimization models are based on techniques such as linear programming. In general, the multiobjective optimization problem can be defined as finding a feasible alternative that yields the most preferred set of values for the objective functions. This problem differs from a single objective because subjective methods are required to determine which alternative is most preferred. A body of literature parallel to that m multiobjective optimization has been developing in the area of multicriterion decision theory. These models are based on classical decision analysis, particularly utility theory. One focus of this research has been the development and testing of procedures for estimating multiattribute utility functions that are consistent with rational decision maker behavior. A utility function provides a model of a decision maker's choice among alternatives. This literature is directly xii MULTIOBJECTIVE OPTIMIZATION applicable to multiobjective optimization and provides much needed insight into the subjective character of that problem.

Authors and Affiliations

  • Operations Research and Strategic Management, Wallace Carroll School of Management, Boston College, Chestnut Hill, USA

    Jeffrey L. Ringuest

Bibliographic Information

  • Book Title: Multiobjective Optimization: Behavioral and Computational Considerations

  • Authors: Jeffrey L. Ringuest

  • DOI: https://doi.org/10.1007/978-1-4615-3612-3

  • Publisher: Springer New York, NY

  • eBook Packages: Springer Book Archive

  • Copyright Information: Springer Science+Business Media New York 1992

  • Hardcover ISBN: 978-0-7923-9236-1Published: 30 June 1992

  • Softcover ISBN: 978-1-4613-6605-8Published: 23 October 2012

  • eBook ISBN: 978-1-4615-3612-3Published: 06 December 2012

  • Edition Number: 1

  • Number of Pages: XV, 169

  • Topics: Operations Research/Decision Theory, Operations Research, Management Science, IT in Business

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