More effective crossover operators for the all-pairs shortest path problem

  • Benjamin Doerr
  • , Daniel Johannsen
  • , Timo Kötzing
  • , Frank Neumann
  • , Madeleine Theile

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

The all-pairs problem is the first non-artificial problem for which it was shown that adding crossover can significantly speed up a mutation-only evolutionary algorithm. Recently, the analysis of this algorithm was refined and it was shown to have an expected optimization time of Θ(n 3.25(logn)0.25). In this work, we study two variants of the algorithm. These are based on two central concepts in recombination, repair mechanisms and parent selection. We show that repairing infeasible offspring leads to an improved expected optimization time of O(n3.2(log n) 0.2). Furthermore, we prove that choosing parents that guarantee feasible offspring results in an optimization time of O(n3 log n).

Original languageEnglish
Title of host publicationParallel Problem Solving from Nature, PPSN XI - 11th International Conference, Proceedings
Pages184-193
Number of pages10
EditionPART 1
DOIs
Publication statusPublished - 12 Nov 2010
Externally publishedYes
Event11th International Conference on Parallel Problem Solving from Nature, PPSN 2010 - Krakow, Poland
Duration: 11 Sept 201015 Sept 2010

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 1
Volume6238 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference11th International Conference on Parallel Problem Solving from Nature, PPSN 2010
Country/TerritoryPoland
CityKrakow
Period11/09/1015/09/10

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