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A parameterized runtime analysis of evolutionary algorithms for MAX-2-SAT

Published:07 July 2012Publication History

ABSTRACT

We investigate the MAX-2-SAT problem and study evolutionary algorithms by parameterized runtime analysis. The parameterized runtime analysis of evolutionary algorithms has been initiated recently and reveals new insights into which type of instances of NP-hard combinatorial optimization problems are hard to solve by evolutionary computing methods. We show that a variant of the (1+1) EA is a fixed-parameter evolutionary algorithm with respect to the standard parameterization for MAX-2-SAT. Furthermore, we study how the dependencies between the variables affect problem difficulty and present fixed-parameter evolutionary algorithms for the MAX-(2,3)-SAT problem where the studied parameter is the diameter of the variable graph.

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    • Published in

      cover image ACM Conferences
      GECCO '12: Proceedings of the 14th annual conference on Genetic and evolutionary computation
      July 2012
      1396 pages
      ISBN:9781450311779
      DOI:10.1145/2330163

      Copyright © 2012 ACM

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      Publication History

      • Published: 7 July 2012

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