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Heuristic Optimization Methods in Industrial Robotics

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Advanced Technologies, Systems, and Applications II (IAT 2017)

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 28))

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Abstract

In industrial robotics is significant numbers of problems that can be optimized which can improve functioning of industrial robots. During the time significant number of optimization methods have been developed in optimization with all their advantages and disadvantages. In this paper are presented genetic algorithm, particle swarm optimization and ant colony as heuristic optimization methods that can be used in industrial robotics.

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References

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Author information

Authors and Affiliations

  1. Technical Faculty, University of Bihać, 77000, Bihać, Bosnia and Herzegovina

    Ermin Husak & Isak Karabegović

Authors
  1. Ermin Husak
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  2. Isak Karabegović
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Corresponding author

Correspondence to Ermin Husak .

Editor information

Editors and Affiliations

  1. Data Science Initiative, UNC Charlotte, Charlotte, USA

    Mirsad Hadžikadić

  2. Faculty of Electrical Engineering, University of Sarajevo, Sarajevo, Bosnia and Herzegovina

    Samir Avdaković

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Husak, E., Karabegović, I. (2018). Heuristic Optimization Methods in Industrial Robotics. In: Hadžikadić, M., Avdaković, S. (eds) Advanced Technologies, Systems, and Applications II. IAT 2017. Lecture Notes in Networks and Systems, vol 28. Springer, Cham. https://doi.org/10.1007/978-3-319-71321-2_84

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  • DOI: https://doi.org/10.1007/978-3-319-71321-2_84

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-71320-5

  • Online ISBN: 978-3-319-71321-2

  • eBook Packages: EngineeringEngineering (R0)

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