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Parallel Distributed Genetic Algorithm for Expensive Multi-Objective Optimization Problems

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Computer Aided Systems Theory - EUROCAST 2009 (EUROCAST 2009)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 5717))

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Abstract

In many Multi-Objective Optimization Problems it is required to evaluate a great number of objective functions and constraints and the calculation effort is very high. The use of parallelism in Multi-Objective Genetic Algorithms is one of the solutions of this problem. In this work we propose an algorithm, based on parallelization scheme using island model with spatially isolated populations. The intent of the proposed paper is to illustrate that modifications made to a selection and resolution processes and to a migration scheme have further improved the efficiency of the algorithm and good distribution of Pareto front.

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Authors and Affiliations

  1. Institute of Computer Engineering, Control and Robotics, Wrocław University of Technology, 11/17 Janiszewskiego St., 50-372, Wrocław, Poland

    Ewa Szlachcic

  2. TETA SA Al, Wisniowa 1, 53-137, Wroclaw, Poland

    Waldemar Zubik

Authors
  1. Ewa Szlachcic
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  2. Waldemar Zubik
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Editors and Affiliations

  1. Instituto Universitario de Ciencias y Tecnologías Cibernéticas, Universidad de Las Palmas de Gran Canaria, Campus de Tafira, 35017, Las Palmas de Gran Canaria, Las Palmas, Spain

    Roberto Moreno-Díaz  & Alexis Quesada-Arencibia  & 

  2. Institute of Systems Science, Johannes Kepler University Linz, Altenbergerstrasse 69, 4040, Linz, Austria

    Franz Pichler

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© 2009 Springer-Verlag Berlin Heidelberg

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Szlachcic, E., Zubik, W. (2009). Parallel Distributed Genetic Algorithm for Expensive Multi-Objective Optimization Problems. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds) Computer Aided Systems Theory - EUROCAST 2009. EUROCAST 2009. Lecture Notes in Computer Science, vol 5717. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-04772-5_120

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  • DOI: https://doi.org/10.1007/978-3-642-04772-5_120

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-04771-8

  • Online ISBN: 978-3-642-04772-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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