Local search in evolutionary algorithms: The impact of the local search frequency

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 4288 LNCS, Issue , 2006, Pages 359-368

  Sudholt, Dirk ^a  

^a TU DORTMUND UNIVERSITY   (Germany)

Author keywords

[No Author keywords available]

Indexed keywords

LOCAL SEARCH; MEMETIC ALGORITHMS; PRACTICAL PROBLEMS; RANDOM SEARCHES; THEORETICAL FOUNDATIONS; WIDE AREA;

COMPUTATIONAL EFFICIENCY; EVOLUTIONARY ALGORITHMS;

COMPUTATION THEORY;

EID: 77249172238     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11940128_37     Document Type: Conference Paper

References (10)

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3. W. E. Hart, N. Krasnogor, and J. E. Smith, editors. Recent Advances in Memetic Algorithms, vol.166 of Studies in Fuzziness and Soft Computing. Springer, 2004.
4. H. R. Lourenço, O. Martin, and T. Stützle. Iterated local search. In Handbook of Metaheuristics, vol.57 of International Series in Operations Research & Management Science, pages 321-353. Kluwer Academic Publishers, Norwell, MA, 2002.
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7. C. Scheideler. Probabilistic Methods for Coordination Problems. HNIVerlagsschriftenreihe 78, University of Paderborn, 2000. Habilitation Thesis, available at http ://www14.in.turn.de/personen/s cheide1er/index.html.en.
8. A. Sinha, Y. Chen, and D. E. Goldberg. Designing efficient genetic and evolutionary algorithm hybrids. In [3], pages 259-288.
9. D. Sudholt. Local search in memetic algorithms: the impact of the local search frequency. Technical Report CI-208/06, Collaborative Research Center 531, University of Dortmund, June 2006. Available at http://sfbci.c8.uni-dortmund. de.
10. D. Sudholt. On the analysis of the (1+1) memetic algorithm. In Proceedings of the Genetic and Evolutionary Computation Conference (GECCO 2006), pages 493-500. ACM Press, New York, NY, 2006.