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Differential Evolution and Tabu Search to Find Multiple Solutions of Multimodal Optimization Problems

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Soft Computing in Industrial Applications

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 223))

Abstract

Many real life optimization problems are multimodal with multiple optima. Evolutionary Algorithms (EA) have successfully been used to solve these problems, but they have the disadvantage since that they converge to only one optimum, even though there are many optima. We proposed a hybrid algorithm combining differential evolution (DE) with tabu search (TS) to find multiple solutions of these problems. The proposed algorithm was tested on optimization problems with multiple optima and the results compared with those provided by the Particle Swarm Optimization (PSO) algorithm.

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Author information

Authors and Affiliations

  1. Graduate Program in Computer Science (PPGI), Federal University of Espírito Santo, Vitória, 29060-970, Brazil

    Erick R. F. A. Schneider

  2. Department of Production Engineering and Graduate Program in Computer Science (PPGI), Federal University of Espírito Santo, Vitoria, 29060-970, Brazil

    Renato A. Krohling

Authors
  1. Erick R. F. A. Schneider
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  2. Renato A. Krohling
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Corresponding author

Correspondence to Erick R. F. A. Schneider .

Editor information

Editors and Affiliations

  1. Department of Computer Science, VŠB-TUO Faculty of Electrical Eng. & Comp. Sci., Ostrava-Poruba, Czech Republic

    Václav Snášel

  2. Department of Computer Science, VŠB-TUO Faculty of Electrical Eng. & Comp. Sci., Ostrava-Poruba, Czech Republic

    Pavel Krömer

  3. Network Design and Research Center, Kyushu Institute of Technology, Fukuoka, Japan

    Mario Köppen

  4. Department of Computer Science, Loughborough University, Lougborough, United Kingdom

    Gerald Schaefer

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Schneider, E.R.F.A., Krohling, R.A. (2014). Differential Evolution and Tabu Search to Find Multiple Solutions of Multimodal Optimization Problems. In: Snášel, V., Krömer, P., Köppen, M., Schaefer, G. (eds) Soft Computing in Industrial Applications. Advances in Intelligent Systems and Computing, vol 223. Springer, Cham. https://doi.org/10.1007/978-3-319-00930-8_6

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  • DOI: https://doi.org/10.1007/978-3-319-00930-8_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-00929-2

  • Online ISBN: 978-3-319-00930-8

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