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A Parameterized Runtime Analysis of Simple Evolutionary Algorithms for Makespan Scheduling

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Parallel Problem Solving from Nature - PPSN XII (PPSN 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7491))

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Abstract

We consider simple multi-start evolutionary algorithms applied to the classical NP-hard combinatorial optimization problem of Makespan Scheduling on two machines. We study the dependence of the runtime of this type of algorithm on three different key hardness parameters. By doing this, we provide further structural insights into the behavior of evolutionary algorithms for this classical problem.

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Authors and Affiliations

  1. School of Computer Science, University of Adelaide, Adelaide, SA, 5005, Australia

    Andrew M. Sutton & Frank Neumann

Authors
  1. Andrew M. Sutton
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  2. Frank Neumann
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Editor information

Editors and Affiliations

  1. Centro de Investigacion y de Estudios, Avanzados del Instituto Politecnico Nacional (CINVESTAV-IPN), Departmento de Computation, Av. IPN No. 2508, Col. San Pedro Zacatenco, 0360, Mexico, D.F., Mexico

    Carlos A. Coello Coello

  2. Department of Mathematics and Computer Science, University of Catania, V.le A. Doria 6, 95125, Catania, Italy

    Vincenzo Cutello  & Mario Pavone  & 

  3. Kanpur Genetic Algorithms Laboratory (KanGAL), Indian Institute of Technology, Kanpur, Kanpur, India

    Kalyanmoy Deb

  4. Department of Computer Science, University of New, Mexico, USA

    Stephanie Forrest

  5. Department of Mathematics and Computer Science, University of Catania, Viale A. Doria 6, 95125, Catania, Italy

    Giuseppe Nicosia

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© 2012 Springer-Verlag Berlin Heidelberg

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Sutton, A.M., Neumann, F. (2012). A Parameterized Runtime Analysis of Simple Evolutionary Algorithms for Makespan Scheduling. In: Coello, C.A.C., Cutello, V., Deb, K., Forrest, S., Nicosia, G., Pavone, M. (eds) Parallel Problem Solving from Nature - PPSN XII. PPSN 2012. Lecture Notes in Computer Science, vol 7491. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-32937-1_6

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  • DOI: https://doi.org/10.1007/978-3-642-32937-1_6

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-32936-4

  • Online ISBN: 978-3-642-32937-1

  • eBook Packages: Computer ScienceComputer Science (R0)

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