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A Memetic Algorithm with Non Gradient-Based Local Search Assisted by a Meta-model

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Parallel Problem Solving from Nature, PPSN XI (PPSN 2010)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 6238))

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Abstract

The development of multi-objective evolutionary algorithms (MOEAs) assisted by meta-models has increased in the last few years. However, the use of local search engines assisted by meta-models for multi-objective optimization has been less common in the specialized literature. In this paper, we propose the use of a local search mechanism which is assisted by a meta-model based on support vector machines. The local search mechanism adopts a free-derivative mathematical programming technique and consists of two main phases: the first generates approximations of the Pareto optimal set. Such solutions are obtained by solving a set of aggregating functions which are defined by different weighted vectors. The second phase generates new solutions departing from those obtained during the first phase. The solutions found by the local search mechanism are incorporated into the evolutionary process of our MOEA. Our experiments show that our proposed approach can produce good quality results with a budget of only 1,000 fitness function evaluations in test problems having between 10 and 30 decision variables.

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Authors and Affiliations

  1. Departamento de Computación, CINVESTAV-IPN (Evolutionary Computation Group), México D.F., 07300, México

    Saúl Zapotecas Martínez & Carlos A. Coello Coello

Authors
  1. Saúl Zapotecas Martínez
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  2. Carlos A. Coello Coello
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Editor information

Editors and Affiliations

  1. Faculty of Electrical Engineering, Automatics, Computer Science and Electronics, Department of ComputerScience, AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Robert Schaefer

  2. Departamento de Lenguajes y Ciencias de la Computación, ETSI Informática, Universidad de Málaga, Campus Teatinos, 29071, Málaga, Spain

    Carlos Cotta

  3. Department of Mathematics and Computer Science, University of Bielsko-Biala, Willowa 2, 43-309, Bielsko-Biala, Poland

    Joanna Kołodziej

  4. Fakultät für Informatik, Technische Universität Dortmund, 44221, Dortmund, Germany

    Günter Rudolph

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© 2010 Springer-Verlag Berlin Heidelberg

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Martínez, S.Z., Coello Coello, C.A. (2010). A Memetic Algorithm with Non Gradient-Based Local Search Assisted by a Meta-model. In: Schaefer, R., Cotta, C., Kołodziej, J., Rudolph, G. (eds) Parallel Problem Solving from Nature, PPSN XI. PPSN 2010. Lecture Notes in Computer Science, vol 6238. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15844-5_58

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  • DOI: https://doi.org/10.1007/978-3-642-15844-5_58

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-15843-8

  • Online ISBN: 978-3-642-15844-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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