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Population Reduction Differential Evolution with Multiple Mutation Strategies in Real World Industry Challenges

  • Conference paper
Swarm and Evolutionary Computation (EC 2012, SIDE 2012)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 7269))

Abstract

This paper presents a novel differential evolution algorithm for optimization of state-of-the-art real world industry challenges. The algorithm includes the self-adaptive jDE algorithm with one of its strongest extensions, population reduction, and is now combined with multiple mutation strategies. The two mutation strategies used are run dependent on the population size, which is reduced with growing function evaluation number. The problems optimized reflect several of the challenges in current industry problems tackled by optimization algorithms nowadays. We present results on all of the 22 problems included in the Problem Definitions for a competition on Congress on Evolutionary Computation (CEC) 2011. Performance of the proposed algorithm is compared to two algorithms from the competition, where the average final best results obtained for each test problem on three different number of total function evaluations allowed are compared.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computer Science, University of Maribor, Smetanova ul. 17, 2000, Maribor, Slovenia, EU

    Aleš Zamuda & Janez Brest

Authors
  1. Aleš Zamuda
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  2. Janez Brest
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Editor information

Editors and Affiliations

  1. Częstochowa University of Technology, Armii Krajowej 36, 42-200, Częstochowa, Poland

    Leszek Rutkowski , Marcin Korytkowski  & Rafał Scherer ,  & 

  2. AGH University of Science and Technology, Mickiewicza 30, 30-059, Kraków, Poland

    Ryszard Tadeusiewicz

  3. Department of Electrical Engineering and Computer Sciences, Computer Science Division, University of California Berkeley, 94720-1776, Berkeley, CA, USA

    Lotfi A. Zadeh

  4. Computational Intelligence Laboratory, Electrical and Computer Engineering, University of Louisville, 405 Lutz Hallz, 40292, Louisville, KY, USA

    Jacek M. Zurada

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© 2012 Springer-Verlag Berlin Heidelberg

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Zamuda, A., Brest, J. (2012). Population Reduction Differential Evolution with Multiple Mutation Strategies in Real World Industry Challenges. In: Rutkowski, L., Korytkowski, M., Scherer, R., Tadeusiewicz, R., Zadeh, L.A., Zurada, J.M. (eds) Swarm and Evolutionary Computation. EC SIDE 2012 2012. Lecture Notes in Computer Science, vol 7269. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-29353-5_18

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  • DOI: https://doi.org/10.1007/978-3-642-29353-5_18

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-29352-8

  • Online ISBN: 978-3-642-29353-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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