Algorithm Engineering

1. Front Matter

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2. Chapter 1. Foundations of Algorithm Engineering

   • Matthias Müller-Hannemann, Stefan Schirra

   Pages 1-15

3. Chapter 2. Modeling

   • Markus Geyer, Benjamin Hiller, Sascha Meinert

   Pages 16-57

4. Chapter 3. Selected Design Issues

   • Sabine Helwig, Falk Hüffner, Ivo Rössling, Maik Weinard

   Pages 58-126

5. Chapter 4. Analysis of Algorithms

   • Heiner Ackermann, Heiko Röglin, Ulf Schellbach, Nils Schweer

   Pages 127-193

6. Chapter 5. Realistic Computer Models

   • Deepak Ajwani, Henning Meyerhenke

   Pages 194-236

7. Chapter 6. Implementation Aspects

   • Marc Mörig, Sven Scholz, Tobias Tscheuschner, Eric Berberich

   Pages 237-289

8. Chapter 7. Libraries

   • Roman Dementiev, Johannes Singler

   Pages 290-324

9. Chapter 8. Experiments

   • Eric Berberich, Matthias Hagen, Benjamin Hiller, Hannes Moser

   Pages 325-388

10. Chapter 9. Case Studies

    • Daniel Delling, Roberto Hoffmann, Maria Kandyba, Anna Schulze

    Pages 389-445

11. Chapter 10. Challenges in Algorithm Engineering

    • Matthias Müller-Hannemann, Stefan Schirra

    Pages 446-453

12. Back Matter

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Algorithms are essential building blocks of computer applications. However, advancements in computer hardware, which render traditional computer models more and more unrealistic, and an ever increasing demand for efficient solution to actual real world problems have led to a rising gap between classical algorithm theory and algorithmics in practice. The emerging discipline of Algorithm Engineering aims at bridging this gap. Driven by concrete applications, Algorithm Engineering complements theory by the benefits of experimentation and puts equal emphasis on all aspects arising during a cyclic solution process ranging from realistic modeling, design, analysis, robust and efficient implementations to careful experiments. This tutorial - outcome of a GI-Dagstuhl Seminar held in Dagstuhl Castle in September 2006 - covers the essential aspects of this process in ten chapters on basic ideas, modeling and design issues, analysis of algorithms, realistic computer models, implementation aspects and algorithmic software libraries, selected case studies, as well as challenges in Algorithm Engineering. Both researchers and practitioners in the field will find it useful as a state-of-the-art survey.

• ad-hoc networks
• algebraic modeling languages
• algorithm design
• algorithmics
• algorithms
• binary optimization
• calculus
• case studies
• computational geometry
• computational testing
• constraint programming
• correctness
• design
• distributed syst
• modeling
• algorithm analysis and problem complexity
• data structures

• Institut für Informatik, Martin-Luther-Universität Halle-Wittenberg, Halle, Germany

  Matthias Müller-Hannemann

• Fakultät für Informatik, Otto-von-Guericke Universität Magdeburg, Magdeburg, Germany

  Stefan Schirra