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Experimental Methods for the Analysis of Optimization Algorithms pp 131–158Cite as

Algorithm Engineering: Concepts and Practice

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Abstract

Over the last years the term algorithm engineering has become wide spread synonym for experimental evaluation in the context of algorithm development. Yet it implies even more. We discuss the major weaknesses of traditional “pen and paper” algorithmics and the ever-growing gap between theory and practice in the context of modern computer hardware and real-world problem instances. We present the key ideas and concepts of the central algorithm engineering cycle that is based on a full feedback loop: It starts with the design of the algorithm, followed by the analysis, implementation, and experimental evaluation. The results of the latter can then be reused for modifications to the algorithmic design, stronger or input-specific theoretic performance guarantees, etc. We describe the individual steps of the cycle, explaining the rationale behind them and giving examples of how to conduct these steps thoughtfully. Thereby we give an introduction to current algorithmic key issues like I/O-efficient or parallel algorithms, succinct data structures, hardware-aware implementations, and others. We conclude with two especially insightful success stories—shortest path problems and text search—where the application of algorithm engineering techniques led to tremendous performance improvements compared with previous state-of-the-art approaches.

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Author information

Authors and Affiliations

  1. Algorithm Engineering, TU Dortmund, Dortmund, Germany

    Markus Chimani & Karsten Klein

Authors
  1. Markus Chimani
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  2. Karsten Klein
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Correspondence to Markus Chimani or Karsten Klein .

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Editors and Affiliations

  1. Institute of Computer Science, Faculty of Computer Science, Cologne University of Applied Sciences, Steinmüllerallee 1, Gummersbach, 51643, Germany

    Thomas Bartz-Beielstein

  2. , Department of Mathematics, University of Southern Denmark, Campusvej 55, Odense, 5230, Denmark

    Marco Chiarandini

  3. CISUC, Department of Informatics Engineering, University of Coimbra, Coimbra, 3030-290, Portugal

    Luís Paquete

  4. Algorithm Engineering, TU Dortmund, Otto-Hahn-Str. 14, Dortmund, 44227, Germany

    Mike Preuss

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Chimani, M., Klein, K. (2010). Algorithm Engineering: Concepts and Practice. In: Bartz-Beielstein, T., Chiarandini, M., Paquete, L., Preuss, M. (eds) Experimental Methods for the Analysis of Optimization Algorithms. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-02538-9_6

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  • DOI: https://doi.org/10.1007/978-3-642-02538-9_6

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  • Online ISBN: 978-3-642-02538-9

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