Abstract
To transform logistics objects in accordance with customer demands, primary logistics functions must be applied (Section 2.1). The applicability of centralised control of supply networks is limited by the complexity, the dynamics, and the distribution of logistics processes (Section 2.3). This finding can be explained by the high number of logistics objects, their manifold parameters, and the dynamic environment. Conventional approaches take a centralised perspective which also requires that all information is centrally available. The paradigm of autonomous logistics aims at overcoming the limitations of conventional control by shifting the perspective to the logistics entities themselves (Section 3.1). These previously inanimate logistics units are provided with logistics objectives by their owners. The entities are then responsible for satisfying their predefined objectives autonomously by requesting execution of the primary logistics functions. Hence, the perspective shifts from individual logistics functions to coordinating all of them.
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References
Dijkstra, E. W. (1959). A Note on Two Problems in Connexion with Graphs. Numerische Mathematik, 1(1), 269–271.
Fischer, K., Schillo, M. & Siekmann, J. H. (2003). Holonic Multiagent Systems: A Foundation for the Organisation of Multiagent Systems. In V. Mařík, D. C. McFarlane & P. Valckenaers (Eds.), 1st International Conference on Industrial Applications of Holonic and Multi-Agent Systems (HoloMAS 2003) (pp. 71–80). Prague, Czech Republic: Springer-Verlag.
Foley, J. D. & Van Dam, A. (1984). Fundamentals of Interactive Computer Graphics. Reading, MA, USA: Addison-Wesley.
Hart, P. E., Nilsson, N. J. & Raphael, B. (1968). A Formal Basis for the Heuristic Determination of Minimum Cost Paths. IEEE Transactions of Systems Science and Cybernetics, 4(2), 100–107.
Li, L. & Horrocks, I. (2004). A Software Framework for Matchmaking Based on SemanticWeb Technology. International Journal of Electronic Commerce, 8(4), 39–60.
Randell, D. A., Cui, Z. & Cohn, A. G. (1992). A Spatial Logic Based on Regions and Connection. In B. Nebel, C. Rich & W. R. Swartout (Eds.), 3rd International Conference on Principles of Knowledge Representation and Reasoning (KR 1992) (pp. 165–176). Cambridge, MA, USA: Morgan Kaufmann Publishers.
Tessaris, S. (2001). Questions and Answers: Reasoning and Querying in Description Logic. Doctoral dissertation, University of Manchester.
Werner, S. (2006). Ontologie-basiertes Agentenmatching. Diplomarbeit, Universität Bremen.
Wooldridge, M. & Jennings, N. R. (1999). The Cooperative Problem Solving Process. Journal of Logic & Computation, 9(4), 563–592.
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Schuldt, A. (2011). Potential for Cooperation in Autonomous Logistics. In: Multiagent Coordination Enabling Autonomous Logistics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-20092-2_5
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DOI: https://doi.org/10.1007/978-3-642-20092-2_5
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