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Clustered enhanced differential evolution for the blocking flow shop scheduling problem

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Abstract

A novel clustered population paradigm is presented in this paper which is based on Chaos principles of edges and attractors. Convergence in evolutionary algorithms is viewed as a manifestation through cyclic dynamics and thus a new population is developed which is clustered and separated through new segregation bias rules. This population is embedded on the Enhanced Differential Evolution and the flow shop scheduling problem with blocking is solved. The two flow shop benchmark problems of Rec/Car/Hel and Taillard are solved with this new approach and the results favorably compared with published results in literature. A total of 49 new upper bounds for the Taillard problems was obtained during experimentation.

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Authors and Affiliations

  1. Faculty of Electrical Engineering and Computing Science, Technical University of Ostrava, Ostrava, Czech Republic

    Donald Davendra & Ivan Zelinka

  2. Tomas Bata University in Zlin, nam. T. G. Masaryka 5555, 760 01, Zlin, Czech Republic

    Magdalena Bialic-Davendra, Roman Senkerik & Roman Jasek

Authors
  1. Donald Davendra
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  2. Ivan Zelinka
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  3. Magdalena Bialic-Davendra
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  4. Roman Senkerik
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  5. Roman Jasek
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Corresponding author

Correspondence to Donald Davendra.

Additional information

Grant Agency of the Czech Republic GACR 102/09/1680.

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Davendra, D., Zelinka, I., Bialic-Davendra, M. et al. Clustered enhanced differential evolution for the blocking flow shop scheduling problem. Cent Eur J Oper Res 20, 679–717 (2012). https://doi.org/10.1007/s10100-011-0198-3

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  • DOI: https://doi.org/10.1007/s10100-011-0198-3

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