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Two Model Checking Approaches to Branch-and-Bound Optimization of a Flow Production System

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Agents and Artificial Intelligence (ICAART 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 10162))

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Abstract

In this paper we introduce a novel application of model checking to find optimal planning solutions for a flow production system. Originally controlled by a multiagent system, the production system consists of autonomous products and asynchronous production stations with limited space for waiting products. In this work, we present two different approaches of application of the Spin model checker to optimize throughput in the given production system. Instead of mapping the multiagent system directly, we model the production line itself as a set of communicating processes. Each communication channel between two processes represents a one-way monorail connection from one station to another. Experiments show that both approaches derive valid and optimized plans with several thousands of steps using constrained branch-and-bound. However, experiments also indicate individual advantages of both approaches.

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Notes

  1. 1.

    http://vas.doc.ic.ac.uk/software/mcmas/.

  2. 2.

    http://plasma.informatik.uni-bremen.de/.

  3. 3.

    http://spinroot.com/spin/whatispin.html.

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Acknowledgements

This research was partly funded by the International Graduate School for Dynamics in Logistics (IGS), University of Bremen, Germany.

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Authors and Affiliations

  1. Institute for Artificial Intelligence, University of Bremen, Bremen, Germany

    Christoph Greulich & Stefan Edelkamp

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  1. Christoph Greulich
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Correspondence to Christoph Greulich .

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  1. Leiden University, Leiden, The Netherlands

    Jaap van den Herik

  2. Polytechnic Institute of Setúbal/INSTICC, Setúbal, Portugal

    Joaquim Filipe

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Greulich, C., Edelkamp, S. (2017). Two Model Checking Approaches to Branch-and-Bound Optimization of a Flow Production System. In: van den Herik, J., Filipe, J. (eds) Agents and Artificial Intelligence. ICAART 2016. Lecture Notes in Computer Science(), vol 10162. Springer, Cham. https://doi.org/10.1007/978-3-319-53354-4_2

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