Parallel Computing in Optimization

1. Front Matter

   Pages i-xix

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2. Models for Parallel Algorithm Design: An Introduction

   • Afonso Ferreira, Michel Morvan

   Pages 1-26

3. Parallel Algorithms and Complexity

   • Martin Fürer

   Pages 27-55

4. A Programmer’s View of Parallel Computers

   • Tor Sørevik

   Pages 57-72

5. Scalable Parallel Algorithms for Sparse Linear Systems

   • Anshul Gupta, George Karypis, Vipin Kumar

   Pages 73-98

6. Object Oriented Mathematical Modelling and Compilation to Parallel Code

   • Niclas Andersson, Peter Fritzson

   Pages 99-182

7. Parallel Algorithms for Network Problems

   • Olof Damberg, Athanasios Migdalas, Sverre Storøy

   Pages 183-238

8. Parallel Branch and Bound — Principles and Personal Experiences

   • Jens Clausen

   Pages 239-267

9. Parallelized Heuristics for Combinatorial Search

   • K. Holmqvist, A. Migdalas, P. M. Pardalos

   Pages 269-294

10. Parallel Cost Approximation Algorithms for Differentiable Optimization

    • Michael Patriksson

    Pages 295-341

11. Parallel Computation of Variational Inequalities and Projected Dynamical Systems with Applications

    • Anna Nagurney

    Pages 343-411

12. Parallel Algorithms for Large-Scale Stochastic Programming

    • Hercules Vladimirou, Stavros A. Zenios

    Pages 413-469

13. Parallel Continuous Non-Convex Optimization

    • Kristina Holmqvist, Athanasios Migdalas, Panos M. Pardalos

    Pages 471-527

14. Deterministic and Stochastic Logarithmic Barrier Function Methods for Neural Network Training

    • Theodore B. Trafalis, Tarek A. Tutunji

    Pages 529-574

15. Back Matter

    Pages 575-587

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During the last three decades, breakthroughs in computer technology have made a tremendous impact on optimization. In particular, parallel computing has made it possible to solve larger and computationally more difficult prob­ lems. This volume contains mainly lecture notes from a Nordic Summer School held at the Linkoping Institute of Technology, Sweden in August 1995. In order to make the book more complete, a few authors were invited to contribute chapters that were not part of the course on this first occasion. The purpose of this Nordic course in advanced studies was three-fold. One goal was to introduce the students to the new achievements in a new and very active field, bring them close to world leading researchers, and strengthen their competence in an area with internationally explosive rate of growth. A second goal was to strengthen the bonds between students from different Nordic countries, and to encourage collaboration and joint research ventures over the borders. In this respect, the course built further on the achievements of the "Nordic Network in Mathematical Programming" , which has been running during the last three years with the support ofthe Nordic Council for Advanced Studies (NorFA). The final goal was to produce literature on the particular subject, which would be available to both the participating students and to the students of the "next generation" .

• algorithms
• Approximation
• complexity
• dynamical systems
• Mathematica
• modeling
• network
• neural networks
• optimization
• parallel computation
• parallel computing
• programming
• Scala

• Division of Optimization, Department of Mathematics, Linköping Institute of Technology, Linköping, Sweden

  Athanasios Migdalas

• Department of Industrial and Systems Engineering, University of Florida, Gainesville, USA

  Panos M. Pardalos

• Department of Informatics, University of Bergen, Bergen, Norway

  Sverre Storøy

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