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Multi-agent-based transport planning in the newspaper industry


  • Böhnlein, Dominik
  • Schweiger, Katharina
  • Tuma, Axel


In many cases of today's planning tasks, the synchronization of production and distribution is becoming increasingly important in order to minimize costs and to maximize customer satisfaction. This is especially the case if transport schedules are closely connected to production schedules, as it is in the newspaper industry--where perishable goods are distributed immediately after production. In order to achieve the above mentioned competing objectives, a special kind of vehicle routing problem, the vehicle routing problem with time windows and cluster-dependent tour starts (VRPTWCD), has to be solved. Moreover, the varying print and post-processing schedules due to unknown editorial deadlines lead to the need for a dynamic online control of the newspaper production and distribution process. In this contribution, the outlined dynamic transport problem is solved online under consideration of unforeseen changes in production schedules. The solution concept is based on a multi-agent system consisting of, amongst others, several Edition and Vehicle Agents. This system is exemplarily applied to a real life application case of one of the largest German newspaper companies. It is shown that a static (centralized) optimization of the underlying problem would even lead to worse results in comparison to the current situation and that the appliance of the multi-agent system is suitable in the newspaper industry.

Suggested Citation

  • Böhnlein, Dominik & Schweiger, Katharina & Tuma, Axel, 2011. "Multi-agent-based transport planning in the newspaper industry," International Journal of Production Economics, Elsevier, vol. 131(1), pages 146-157, May.
  • Handle: RePEc:eee:proeco:v:131:y:2011:i:1:p:146-157

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    References listed on IDEAS

    1. Chiang, Wen-Chyuan & Russell, Robert & Xu, Xiaojing & Zepeda, David, 2009. "A simulation/metaheuristic approach to newspaper production and distribution supply chain problems," International Journal of Production Economics, Elsevier, vol. 121(2), pages 752-767, October.
    2. Akanle, O.M. & Zhang, D.Z., 2008. "Agent-based model for optimising supply-chain configurations," International Journal of Production Economics, Elsevier, vol. 115(2), pages 444-460, October.
    3. Gunasekaran, Angappa & Lai, Kee-hung & Edwin Cheng, T.C., 2008. "Responsive supply chain: A competitive strategy in a networked economy," Omega, Elsevier, vol. 36(4), pages 549-564, August.
    4. Van Buer, Michael G. & Woodruff, David L. & Olson, Rick T., 1999. "Solving the medium newspaper production/distribution problem," European Journal of Operational Research, Elsevier, vol. 115(2), pages 237-253, June.
    5. M. Ruth & K. Donaghy & P. Kirshen, 2006. "Introduction," Chapters,in: Regional Climate Change and Variability, chapter 1 Edward Elgar Publishing.
    6. Anosike, A.I. & Zhang, D.Z., 2009. "An agent-based approach for integrating manufacturing operations," International Journal of Production Economics, Elsevier, vol. 121(2), pages 333-352, October.
    7. Mantel, R. J. & Fontein, M., 1993. "A practical solution to a newspaper distribution problem," International Journal of Production Economics, Elsevier, vol. 30(1), pages 591-599, July.
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    Cited by:

    1. Olivier Cardin & Damien Trentesaux & André Thomas & Pierre Castagna & Thierry Berger & Hind Bril El-Haouzi, 0. "Coupling predictive scheduling and reactive control in manufacturing hybrid control architectures: state of the art and future challenges," Journal of Intelligent Manufacturing, Springer, vol. 0, pages 1-15.


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