Optimization Software Class Libraries

  • Stefan Voß
  • David L. Woodruff

Part of the Operations Research/Computer Science Interfaces Series book series (ORCS, volume 18)

Table of contents

  1. Front Matter
    Pages i-x
  2. Stefan Voß, David L. Woodruff
    Pages 1-24
  3. Martin S. Jones, Geoff P. McKeown, Vic J. Rayward-Smith
    Pages 25-58
  4. Alexandre A. Andreatta, Sérgio E. R. Carvalho, Celso C. Ribeiro
    Pages 59-79
  5. Andreas Fink, Stefan Voß
    Pages 81-154
  6. Luca Di Gaspero, Andrea Schaerf
    Pages 155-175
  7. Christos Voudouris, Raphaël Dorne
    Pages 177-191
  8. Manuel Laguna, Rafael Martí
    Pages 193-218
  9. Paul Shaw, Vincent Furnon, Bruno De Backer
    Pages 219-261
  10. Pascal Van Hentenryck, Laurent Michel
    Pages 263-294
  11. Andrew R. Pain, Colin R. Reeves
    Pages 295-329
  12. Back Matter
    Pages 331-360

About this book

Introduction

Optimization problems in practice are diverse and evolve over time, giving rise to - quirements both for ready-to-use optimization software packages and for optimization software libraries, which provide more or less adaptable building blocks for app- cation-specific software systems. In order to apply optimization methods to a new type of problem, corresponding models and algorithms have to be “coded” so that they are accessible to a computer. One way to achieve this step is the use of a mod- ing language. Such modeling systems provide an excellent interface between models and solvers, but only for a limited range of model types (in some cases, for example, linear) due, in part, to limitations imposed by the solvers. Furthermore, while m- eling systems especially for heuristic search are an active research topic, it is still an open question as to whether such an approach may be generally successful. Modeling languages treat the solvers as a “black box” with numerous controls. Due to variations, for example, with respect to the pursued objective or specific problem properties, - dressing real-world problems often requires special purpose methods. Thus, we are faced with the difficulty of efficiently adapting and applying appropriate methods to these problems. Optimization software libraries are intended to make it relatively easy and cost effective to incorporate advanced planning methods in application-specific software systems. A general classification provides a distinction between callable packages, nume- cal libraries, and component libraries.

Keywords

algorithms bioinformatics combinatorial optimization computer genetic algorithms modeling optimization programming

Editors and affiliations

  • Stefan Voß
    • 1
  • David L. Woodruff
    • 2
  1. 1.Braunschweig University of TechnologyGermany
  2. 2.University of CaliforniaDavisUSA

Bibliographic information

  • DOI https://doi.org/10.1007/b101931
  • Copyright Information Kluwer Academic Publishers 2002
  • Publisher Name Springer, Boston, MA
  • eBook Packages Springer Book Archive
  • Print ISBN 978-1-4020-7002-0
  • Online ISBN 978-0-306-48126-0
  • Series Print ISSN 1387-666X
  • About this book