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GRASP for Minimizing the Ergonomic Risk Range in Mixed-Model Assembly Lines

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Advances in Artificial Intelligence (CAEPIA 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9868))

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Abstract

This research examines an assembly line balancing problem and compares the linear programing with a Greedy Randomized Adaptive Search Procedure (GRASP). The problem focuses on minimizing the absolute average deviation for the ergonomic risk between the set of workstations of the line, considering a fixed cycle time and an available space per station. However, the final objective is to obtain line configurations with the lowest possible ergonomic risk, and the lowest discrepancy for the risk level between all stations. Although GRASP does not win linear programing, in all cases, it shows competitive.

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References

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Acknowledgment

This work was funded by the Ministerio de Economía y Competitividad (Spanish Government) through the FHI-SELM2 (TIN2014-57497-P) project.

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Authors and Affiliations

  1. Research Group OPE-PROTHIUS, Dpto. de Organización de Empresas, Universitat Politècnica de Catalunya BarcelonaTech (UPC), Avda. Diagonal, 647, 08028, Barcelona, Spain

    Joaquín Bautista, Rocío Alfaro-Pozo & Cristina Batalla-García

Authors
  1. Joaquín Bautista
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  2. Rocío Alfaro-Pozo
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  3. Cristina Batalla-García
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Corresponding author

Correspondence to Joaquín Bautista .

Editor information

Editors and Affiliations

  1. Artificial Intelligence Center, University of Oviedo, Gijón, Spain

    Oscar Luaces

  2. University of Castilla-La Mancha , Albacete, Spain

    José A. Gámez

  3. Public University of Navarre , Pamplona, Spain

    Edurne Barrenechea

  4. Universidad Pablo de Olavide , Sevilla, Spain

    Alicia Troncoso

  5. Public University of Navarre , Pamplona, Navarra, Spain

    Mikel Galar

  6. University of Salamanca , Salamanca, Spain

    Héctor Quintián

  7. University of Salamanca , Salamanca, Spain

    Emilio Corchado

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Bautista, J., Alfaro-Pozo, R., Batalla-García, C. (2016). GRASP for Minimizing the Ergonomic Risk Range in Mixed-Model Assembly Lines. In: Luaces , O., et al. Advances in Artificial Intelligence. CAEPIA 2016. Lecture Notes in Computer Science(), vol 9868. Springer, Cham. https://doi.org/10.1007/978-3-319-44636-3_37

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  • DOI: https://doi.org/10.1007/978-3-319-44636-3_37

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-44635-6

  • Online ISBN: 978-3-319-44636-3

  • eBook Packages: Computer ScienceComputer Science (R0)

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