Smoothed Analysis of Local Search Algorithms

  • Bodo Manthey
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9214)


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.


Local Search Approximation Ratio Travel Salesman Problem Local Search Algorithm Iterative Close Point 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  1. 1.Department of Applied MathematicsUniversity of TwenteEnschedeThe Netherlands

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