Table of contents

  1. Front Matter
    Pages i-xxvi
  2. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 1-29
  3. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 31-69
  4. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 71-125
  5. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 127-179
  6. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 181-220
  7. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 221-262
  8. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 263-321
  9. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 323-384
  10. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 385-432
  11. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 433-476
  12. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 477-513
  13. Steven A. Gabriel, Antonio J. Conejo, J. David Fuller, Benjamin F. Hobbs, Carlos Ruiz
    Pages 515-560
  14. Back Matter
    Pages 561-629

About this book

Introduction

This addition to the ISOR series  introduces complementarity models in a straightforward and approachable manner and uses them to carry out an in-depth analysis of energy markets, including formulation issues and solution techniques.   In a nutshell, complementarity models generalize:
a. optimization problems via their Karush-Kuhn-Tucker conditions
b. non-cooperative games in which each player may be solving a separate but related optimization problem with potentially overall system constraints (e.g., market-clearing conditions)
c. economic and engineering problems that aren’t specifically derived from optimization problems (e.g., spatial price equilibria)
d. problems in which both primal and dual variables (prices) appear in the original formulation (e.g., The National Energy Modeling System (NEMS) or its precursor, PIES).
As such, complementarity models are a very general and flexible modeling format.

A natural question is why concentrate on energy markets for this complementarity approach?  As it turns out, energy or other markets that have game theoretic aspects are best modeled by complementarity problems.  The reason is that the traditional perfect competition approach no longer applies due to deregulation and restructuring of these markets and thus the corresponding optimization problems may no longer hold.  Also, in some instances it is important in the original model formulation to involve both primal variables (e.g., production) as well as dual variables (e.g., market prices) for public and private sector energy planning.  Traditional optimization problems can not directly handle this mixing of primal and dual variables but complementarity models can and this makes them all that more effective for decision-makers.

Keywords

Complementarity Modeling Decision Making Energy Markets Equilibrium Operations Research

Authors and affiliations

  • Steven A. Gabriel
    • 1
  • Antonio J. Conejo
    • 2
  • J. David Fuller
    • 3
  • Benjamin F. Hobbs
    • 4
  • Carlos Ruiz
    • 5
  1. 1., Department of Civil and Environmental EnUniversity of MarylandCollege ParkUSA
  2. 2.University of Castilla - La ManchaCiudad RealSpain
  3. 3., Department of Management SciencesUniversity of WaterlooWaterlooCanada
  4. 4., Department of Geography & EnvironmentalThe Johns Hopkins UniversityBaltimoreUSA
  5. 5.École Centrale Paris and SupélecChâtenay-MalabryFrance

Bibliographic information

  • DOI https://doi.org/10.1007/978-1-4419-6123-5
  • Copyright Information Springer Science+Business Media New York 2013
  • Publisher Name Springer, New York, NY
  • eBook Packages Business and Economics
  • Print ISBN 978-1-4419-6122-8
  • Online ISBN 978-1-4419-6123-5
  • Series Print ISSN 0884-8289
  • About this book