Research Output

Analysing the performance of migrating birds optimisation approaches for large scale continuous problems

  We present novel algorithmic schemes for dealing with large
scale continuous problems. They are based on the recently proposed
population-based meta-heuristics Migrating Birds Optimisation (mbo) and Multi-leader Migrating Birds Optimisation (mmbo), that have shown to be effective for solving combinatorial problems. The main objective of the current paper is twofold. First, we introduce a novel neighbour generating operator based on Differential Evolution (de) that allows to produce new individuals in the continuous decision space starting from those belonging to the current population. Second, we evaluate the performance of mbo and mmbo by incorporating our novel operator to them. Hence, mbo and mmbo are enabled for solving continuous problems. Comparisons are carried out by applying both aforementioned schemes
to a set of well-known large scale functions.

  • Date:

    30 November 2015

  • Publication Status:

    Published

  • Publisher

    Springer

  • Library of Congress:

    QA75 Electronic computers. Computer science

  • Dewey Decimal Classification:

    004.2 Systems analysis, design & performance

Citation

Lalla-Ruiz, E., Segredo, E., Voss, S., Hart, E. & Paechter, B. (2015). Analysing the performance of migrating birds optimisation approaches for large scale continuous problems. In Parallel Problem Solving from Nature – PPSN XIV, 134-144. ISBN 978-3-319-45823-6; 978-3-319-45822-9

Authors

Keywords

Migrating birds optimization; population-based meta-heuristics; MMBO (Multi-leader Migrating Birds Optimisation); global optimization problems;

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