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Workshop on Algorithms and Data Structures

WADS 2015: Algorithms and Data Structures pp 518–527Cite as

Smoothed Analysis of Local Search Algorithms

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Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9214))

Abstract

Smoothed analysis is a method for analyzing the performance of algorithms for which classical worst-case analysis fails to explain the performance observed in practice. Smoothed analysis has been applied to explain the performance of a variety of algorithms in the last years.

One particular class of algorithms where smoothed analysis has been used successfully are local search algorithms. We give a survey of smoothed analysis, in particular applied to local search algorithms.

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Author information

Authors and Affiliations

  1. Department of Applied Mathematics, University of Twente, Enschede, The Netherlands

    Bodo Manthey

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  1. Bodo Manthey
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Correspondence to Bodo Manthey .

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Editors and Affiliations

  1. Carleton University, Ottawa, Canada

    Frank Dehne

  2. Carleton University, Ottawa, Canada

    Jörg-Rüdiger Sack

  3. University of Victoria, Victoria, Canada

    Ulrike Stege

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Manthey, B. (2015). Smoothed Analysis of Local Search Algorithms. In: Dehne, F., Sack, JR., Stege, U. (eds) Algorithms and Data Structures. WADS 2015. Lecture Notes in Computer Science(), vol 9214. Springer, Cham. https://doi.org/10.1007/978-3-319-21840-3_43

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  • DOI: https://doi.org/10.1007/978-3-319-21840-3_43

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  • Online ISBN: 978-3-319-21840-3

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