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Solving a robotic assembly line balancing problem using efficient hybrid methods

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Abstract

In this paper we are studying a robotic assembly line balancing problem. The goal is to maximize the efficiency of the line and to balance the different tasks between the robots by defining the suitable tasks and components to assign to each robot. We are interested in a robotic line which consists of seizing the products on a moving conveyor and placing them on different location points. The performances evaluations of the system are done using a discret event simulation model. This latter has been developed with C++ language. As in our industrial application we are bounded by the execution time, we propose some resolution methods which define the suitable component and point positions in order to define the strategy of pick and place for each robot. These methods are based on the ant colony optimization, particle swarm optimization and genetic algorithms. To enhance the quality of the developed algorithms and to avoid local optima, we have coupled these algorithms with guided local search. After that, an exact method based on full enumeration is also developed to assess the quality of the developed methods. Then, we try to select the best algorithm which is able to get the best solutions with a small execution time. This is the main advantage of our methods compared to exact methods. This fact represents a great interest taking in consideration that the selected methods are used to manage the functioning of real industrial robotic assembly lines. Numerical results show that the selected algorithm performs optimally for the tested instances in a reasonable computation time and satisfies the industrial constraint.

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Acknowledgments

This research was supported by ARIES Packaging (France). The authors are also very grateful to the national association of technical research (ANRT) in France.

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Authors and Affiliations

  1. ARIES Packaging, Technopole de l’Aube en Champagne, Rosires, France

    Slim Daoud, Hicham Chehade, Farouk Yalaoui & Lionel Amodeo

  2. ICD, LOSI, Troyes University of Technology, UMR 6281, CNRS, Troyes, France

    Slim Daoud, Hicham Chehade, Farouk Yalaoui & Lionel Amodeo

Authors
  1. Slim Daoud
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  2. Hicham Chehade
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  3. Farouk Yalaoui
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  4. Lionel Amodeo
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Correspondence to Hicham Chehade.

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Daoud, S., Chehade, H., Yalaoui, F. et al. Solving a robotic assembly line balancing problem using efficient hybrid methods. J Heuristics 20, 235–259 (2014). https://doi.org/10.1007/s10732-014-9239-0

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  • DOI: https://doi.org/10.1007/s10732-014-9239-0

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