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A Tool for an Analysis of the Dynamic Behavior of Logistic Systems with the Instruments of Complex Networks

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Dynamics in Logistics (LDIC 2018)

Abstract

It is known that the whole is more than the sum of its parts. In production for each machine a lot of information is available due to today’s integration of automatic data recording. In this context, one way of representing the whole is the modeling as a complex network. Yet, present complex network analysis tools can either not manage the amount of data of such systems or neglect their dynamic behavior. Therefore, we present a tool, which meets these requirements of the logistic field, and demonstrate its abilities for a real-world example.

T. Funke—This work was funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) BE 5538/2-1.

T. Becker—This work has been supported by the Institutional Strategy of the University of Bremen, funded by the German Excellence Initiative.

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Notes

  1. 1.

    https://github.com/funket/dyneta.

References

  1. Albert, R., Barabási, A.L.: Statistical mechanics of complex networks. Rev. Mod. Phys. 74, 47–97 (2002). https://link.aps.org/doi/10.1103/RevModPhys.74.47

    Article  MathSciNet  MATH  Google Scholar 

  2. Bastian, M., Heymann S., Jacomy M.: Gephi: an open source software for exploring and manipulating networks. In: International AAAI Conference on Weblogs and Social Media (2009). http://www.aaai.org/ocs/index.php/ICWSM/09/paper/view/154

  3. Beber, M.E., Becker, T.: Towards an understanding of the relation between topological characteristics and dynamic behavior in manufacturing networks. Procedia CIRP 19, 21–26 (2014). http://www.sciencedirect.com/science/article/pii/S2212827114006337, 2nd CIRP Robust Manufacturing Conference (RoMac 2014)

    Article  Google Scholar 

  4. Becker, T., Meyer, M., Windt, K.: A manufacturing systems network model for the evaluation of complex manufacturing systems. Int. J. Product. Perform. Manag. 63(3), 324–340 (2014). https://doi.org/10.1108/IJPPM-03-2013-0047

    Article  Google Scholar 

  5. Boccaletti, S., Latora, V., Moreno, Y., Chavez, M., Hwang, D.U.: Complex networks: structure and dynamics. Phys. Rep. 424(4), 175–308 (2006). http://www.sciencedirect.com/science/article/pii/S037015730500462X

    Article  MathSciNet  MATH  Google Scholar 

  6. Bryan, D.L., O’Kelly, M.E.: Hub-and-spoke networks in air transportation: an analytical review. J. Reg. Sci. 39(2), 275–295 (1999). https://doi.org/10.1111/1467-9787.00134

    Article  Google Scholar 

  7. Clauset, A., Shalizi, C.R., Newman, M.E.J.: Power-law distributions in empirical data. SIAM Rev. 51(4), 661–703 (2009). https://doi.org/10.1137/070710111

    Article  MathSciNet  MATH  Google Scholar 

  8. Ellson, J., Gansner, E., Koutsofios, L., North, S.C., Woodhull, G.: Graphviz - open source graph drawing tools. In: International Symposium on Graph Drawing, pp. 483–484. Springer, Heidelberg (2001)

    Google Scholar 

  9. Hagberg, A., Swart, P., Schult, D.: Exploring network structure, dynamics, and function using networkx. Technical report, Los Alamos National Laboratory (LANL) (2008)

    Google Scholar 

  10. Latora, V., Marchiori, M.: Efficient behavior of small-world networks. Phys. Rev. Lett. 87, 198701 (2001). https://link.aps.org/doi/10.1103/PhysRevLett.87.198701

    Article  Google Scholar 

  11. Newman, M.E.J.: Assortative mixing in networks. Phys. Rev. Lett. 89, 208701 (2002). https://link.aps.org/doi/10.1103/PhysRevLett.89.208701

    Article  Google Scholar 

  12. Sayama, H.: Pycx: a python-based simulation code repository for complex systems education. Complex Adapt. Syst. Model. 1(1), 2 (2013). https://doi.org/10.1186/2194-3206-1-2

    Article  Google Scholar 

  13. Sayama, H.: Introduction to the Modeling and Analysis of Complex Systems. Open SUNY Textbooks (2015)

    Google Scholar 

  14. Smith, M., Milic-Frayling, N., Shneiderman, B., Mendes Rodrigues, E., Leskovec, J., Dunne, C.: Nodexl: a free and open network overview, discovery and exploration add-in for excel 2007/2010 (2010)

    Google Scholar 

  15. Watts, D.J., Strogatz, S.H.: Collective dynamics of ‘small-world’ networks. Nature 393(6684), 440–442 (1998). https://doi.org/10.1038/30918

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Correspondence to Thorben Funke or Till Becker .

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Funke, T., Becker, T. (2018). A Tool for an Analysis of the Dynamic Behavior of Logistic Systems with the Instruments of Complex Networks. In: Freitag, M., Kotzab, H., Pannek, J. (eds) Dynamics in Logistics. LDIC 2018. Lecture Notes in Logistics. Springer, Cham. https://doi.org/10.1007/978-3-319-74225-0_57

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  • DOI: https://doi.org/10.1007/978-3-319-74225-0_57

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