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A Genetic Algorithm-Based Heuristic for Part-Feeding Mobile Robot Scheduling Problem

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Part of the book series: Advances in Intelligent and Soft Computing ((AINSC,volume 157))

Abstract

This present study deals with the problem of sequencing feeding tasks of a single mobile robot with manipulation arm which is able to provide parts or components for feeders of machines in a manufacturing cell. The mobile robot has to be scheduled in order to keep machines within the cell producing products without any shortage of parts. A method based on the characteristics of feeders and inspired by the (s, Q) inventory system, is thus applied to define time windows for feeding tasks of the robot. The performance criterion is to minimize total traveling time of the robot in a given planning horizon. A genetic algorithm-based heuristic is developed to find the near optimal solution for the problem. A case study is implemented at an impeller production line in a factory to demonstrate the result of the proposed approach.

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Correspondence to Quang-Vinh Dang .

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© 2012 Springer-Verlag Berlin Heidelberg

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Dang, QV., Nielsen, I.E., Bocewicz, G. (2012). A Genetic Algorithm-Based Heuristic for Part-Feeding Mobile Robot Scheduling Problem. In: Rodríguez, J., Pérez, J., Golinska, P., Giroux, S., Corchuelo, R. (eds) Trends in Practical Applications of Agents and Multiagent Systems. Advances in Intelligent and Soft Computing, vol 157. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28795-4_10

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  • DOI: https://doi.org/10.1007/978-3-642-28795-4_10

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28794-7

  • Online ISBN: 978-3-642-28795-4

  • eBook Packages: EngineeringEngineering (R0)

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