Constraint Programming and Decision Making

  • Martine Ceberio
  • Vladik Kreinovich

Part of the Studies in Computational Intelligence book series (SCI, volume 539)

Table of contents

  1. Front Matter
    Pages 1-12
  2. E. Cabral Balreira, Olga Kosheleva, Vladik Kreinovich
    Pages 1-7
  3. Martine Ceberio, Vladik Kreinovich
    Pages 15-18
  4. Juan C. Figueroa-García, Germán Hernández
    Pages 19-34
  5. Aline Jaimes, Craig Tweedy, Tanja Magoc, Vladik Kreinovich, Martine Ceberio
    Pages 61-65
  6. Olga Kosheleva, Martine Ceberio, Vladik Kreinovich
    Pages 75-78
  7. Tanja Magoč, François Modave
    Pages 97-109
  8. Paden Portillo, Martine Ceberio, Vladik Kreinovich
    Pages 137-141
  9. Uram Anibal Sosa Aguirre, Martine Ceberio, Vladik Kreinovich
    Pages 175-179
  10. Laura P. Swiler, Patricia D. Hough, Peter Qian, Xu Xu, Curtis Storlie, Herbert Lee
    Pages 181-202
  11. Back Matter
    Pages 209-209

About this book


In many application areas, it is necessary to make effective decisions under constraints. Several area-specific techniques are known for such decision problems; however, because these techniques are area-specific, it is not easy to apply each technique to other applications areas. Cross-fertilization between different application areas is one of the main objectives of the annual International Workshops on Constraint Programming and Decision Making. Those workshops, held in the US (El Paso, Texas), in Europe (Lyon, France), and in Asia (Novosibirsk, Russia), from 2008 to 2012, have attracted researchers and practitioners from all over the world. This volume presents extended versions of selected papers from those workshops. These papers deal with all stages of decision making under constraints: (1) formulating the problem of multi-criteria decision making in precise terms, (2) determining when the corresponding decision problem is algorithmically solvable; (3) finding the corresponding algorithms, and making these algorithms as efficient as possible; and (4) taking into account interval, probabilistic, and fuzzy uncertainty inherent in the corresponding decision making problems. The resulting application areas include environmental studies (selecting the best location for a meteorological tower), biology (selecting the most probable evolution history of a species), and engineering (designing the best control for a magnetic levitation train).


Computational Intelligence Constraint Programming Decision Making Decision Making Under Constraints

Editors and affiliations

  • Martine Ceberio
    • 1
  • Vladik Kreinovich
    • 2
  1. 1.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA
  2. 2.Department of Computer ScienceUniversity of Texas at El PasoEl PasoUSA

Bibliographic information

  • DOI
  • Copyright Information Springer International Publishing Switzerland 2014
  • Publisher Name Springer, Cham
  • eBook Packages Engineering Engineering (R0)
  • Print ISBN 978-3-319-04279-4
  • Online ISBN 978-3-319-04280-0
  • Series Print ISSN 1860-949X
  • Series Online ISSN 1860-9503
  • Buy this book on publisher's site
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