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Fitness Distance Correlation and Search Space Analysis for Permutation Based Problems

  • Conference paper
Evolutionary Computation in Combinatorial Optimization (EvoCOP 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6022))

Abstract

The fitness distance correlation (FDC) as a measure for problem difficulty was first introduced by Forrest and Jones. It was applied to many binary coded problems. This method is now applied to permutation based problems. As demanded by Schiavinotto and Stützle, the distance in a search space is calculated by regarding the steps of the (neighborhood) operator. In this paper the five most common operators for permutations are analyzed on symmetric and asymmetric TSP instances. In addition a local quality measure, the point quality (PQ) is proposed as a supplement to the global FDC. With this local measure more characteristics and differences can be investigated. Some experimental results are illustrating these concepts.

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Author information

Authors and Affiliations

  1. University of Stuttgart, FMI, Universitätstr. 38, 70569, Stuttgart, Germany

    Botond Draskoczy

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  1. Botond Draskoczy
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Editors and Affiliations

  1. Department of Computing, University of Bradford, BD7 1DP, Bradford, UK

    Peter Cowling

  2. Department of Business Administration and Computer Science, FH-Hannover - University of Applied Sciences and Arts, Ricklinger Stadtweg 120, 30459, Hannover, Germany

    Peter Merz

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Draskoczy, B. (2010). Fitness Distance Correlation and Search Space Analysis for Permutation Based Problems. In: Cowling, P., Merz, P. (eds) Evolutionary Computation in Combinatorial Optimization. EvoCOP 2010. Lecture Notes in Computer Science, vol 6022. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-12139-5_5

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  • DOI: https://doi.org/10.1007/978-3-642-12139-5_5

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-12138-8

  • Online ISBN: 978-3-642-12139-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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