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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4638))

Abstract

We consider a possible scenario of experimental analysis on heuristics for optimization: identifying the contribution of local search components when algorithms are evaluated on the basis of solution quality attained.

We discuss the experimental designs with special focus on the role of the test instances in the statistical analysis. Contrary to previous practice of modeling instances as a blocking factor, we treat them as a random factor. Together with algorithms, or their components, which are fixed factors, this leads naturally to a mixed ANOVA model. We motivate our choice and illustrate the application of the mixed model on a study of local search for the 2-edge-connectivity problem.

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Thomas Stützle Mauro Birattari Holger H. Hoos

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© 2007 Springer-Verlag Berlin Heidelberg

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Bang-Jensen, J., Chiarandini, M., Goegebeur, Y., Jørgensen, B. (2007). Mixed Models for the Analysis of Local Search Components. In: Stützle, T., Birattari, M., H. Hoos, H. (eds) Engineering Stochastic Local Search Algorithms. Designing, Implementing and Analyzing Effective Heuristics. SLS 2007. Lecture Notes in Computer Science, vol 4638. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74446-7_7

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  • DOI: https://doi.org/10.1007/978-3-540-74446-7_7

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-74445-0

  • Online ISBN: 978-3-540-74446-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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