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Simulation and optimization of robotic tasks for UV treatment of diseases in horticulture

Author

Listed:
  • Merouane Mazar

    (LINEACT - CESI. 80, rue Edmund Halley, Rouen Madrillet Innovation)

  • M’hammed Sahnoun

    (LINEACT - CESI. 80, rue Edmund Halley, Rouen Madrillet Innovation)

  • Belgacem Bettayeb

    (LINEACT - CESI. 8, boulevard Louis XIV)

  • Nathalie Klement

    (LISPEN, Arts et Métiers, HeSam. École Nationale Supérieure d’Arts et Métiers. 8, boulevard Louis XIV)

  • Anne Louis

    (LINEACT - CESI. 80, rue Edmund Halley, Rouen Madrillet Innovation)

Abstract

Robotization is increasingly used in the agriculture since the last few decades. It is progressively replacing the human workforce that is deserting the agricultural sector, partly because of the harshness of its activities and health risks they may present. Moreover, robotization aims to improve efficiency and competitiveness of the agricultural sector. However, it leads to several research and development challenges regarding robots supervision, control and optimization. This paper presents a simulation and optimization approach for the optimization of robotized treatment tasks using type-c ultraviolet radiation in horticulture. The optimization of tasks scheduling problem is formalized and a heuristic and a genetic algorithms are proposed to solve it. These algorithms are evaluated compared to an exact method using a multi-agent-based simulation approach. The simulator takes into account the evolution of the disease during time and simulates the execution of treatment tasks by the robot.

Suggested Citation

  • Merouane Mazar & M’hammed Sahnoun & Belgacem Bettayeb & Nathalie Klement & Anne Louis, 2022. "Simulation and optimization of robotic tasks for UV treatment of diseases in horticulture," Operational Research, Springer, vol. 22(1), pages 49-75, March.
  • Handle: RePEc:spr:operea:v:22:y:2022:i:1:d:10.1007_s12351-019-00541-w
    DOI: 10.1007/s12351-019-00541-w
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    References listed on IDEAS

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    1. Michael Schneider & Andreas Stenger & Dominik Goeke, 2014. "The Electric Vehicle-Routing Problem with Time Windows and Recharging Stations," Transportation Science, INFORMS, vol. 48(4), pages 500-520, November.
    2. Schneider, M. & Stenger, A. & Goeke, D., 2014. "The Electric Vehicle Routing Problem with Time Windows and Recharging Stations," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62382, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    3. Mohammed Dahane & M’hammed Sahnoun & Belgacem Bettayeb & David Baudry & Hamza Boudhar, 2017. "Impact of spare parts remanufacturing on the operation and maintenance performance of offshore wind turbines: a multi-agent approach," Journal of Intelligent Manufacturing, Springer, vol. 28(7), pages 1531-1549, October.
    4. Warren Powell & Joel Shapiro & Hugo Simao, 2001. "A Representational Paradigm for Dynamic Resource Transformation Problems," Annals of Operations Research, Springer, vol. 104(1), pages 231-279, April.
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