With the Physical Internet (PI), a global economic transformation towards a more holistic consideration and collaboration of different agents is promoted. Its goal is the implementation of global sustainable logistics by increasing the utilization of available resources. This should be reached by developing a network in which goods of different organizations are transported, stored and handled. One aspect of the PI is the optimization of the transport procedure. In this paper, potential optimization models for a subset of three key elements of the PI, the containers, movers (all kinds of transportation means), and nodes (all kinds of locations), are presented. Moreover, corresponding algorithmic approaches are proposed. The novel modeling approach of optimization networks (ON) with the objective of finding an overall optimized solution considering the involved interrelated subtasks in a holistic sense is compared to highly reactive solution methods based on rules that are learned offline. With the proposed approaches, interoperability between different (economic) agents and (software) systems is supported. The goal of multidisciplinary collaboration of different participants and their integration into one PI network should be approached.
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Ahuja, R.K., Magnanti, T.L., Orlin, J.B.: Network Flows: Theory, Algorithms, and Applications. Prentice Hall, Upper Saddle River (1993)
MATH
2.
Beham, A., Fechter, J., Kommenda, M., Wagner, S., Winkler, S.M., Affenzeller, M.: Optimization strategies for integrated knapsack and traveling salesman problems. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds.) EUROCAST 2015. LNCS, vol. 9520, pp. 359–366. Springer, Cham (2015).
https://doi.org/10.1007/978-3-319-27340-2_45CrossRef
3.
Beham, A., Kofler, M., Wagner, S., Affenzeller, M.: Agent-based simulation of dispatching rules in dynamic pickup and delivery problems. In: 2009 2nd International Logistics and Industrial Informatics, LINDI 2009, pp. 1–6. IEEE (2009)
4.
Fazili, M., Venkatadri, U., Cyrus, P., Tajbakhsh, M.: Physical internet, conventional and hybrid logistic systems: a routing optimisation-based comparison using the eastern canada road network case study. Int. J. Prod. Res.
55(9), 2703–2730 (2017)
CrossRef
5.
Fu, M.C., Glover, F.W., April, J.: Simulation optimization: a review, new developments, and applications. In: 2005 Proceedings of the winter Simulation Conference, p. 13. IEEE (2005)
6.
Hall, A., Hippler, S., Skutella, M.: Multicommodity flows over time: Efficient algorithms and complexity. Theoret. Comput. Sci.
379(3), 387–404 (2007)
MathSciNetCrossRefMATH
7.
Hauder, V.A., Karder, J., Beham, A., Affenzeller, M.: A general solution approach for the location routing problem. In: EUROCAST (2017)
8.
Karder, J., Beham, A., Wagner, S., Affenzeller, M.: Solving the traveling thief problem using orchestration in optimization networks. In: EUROCAST (2017)
Montreuil, B.: Toward a physical internet: meeting the global logistics sustainability grand challenge. Logistics Res.
3(2–3), 71–87 (2011)
CrossRef
11.
Montreuil, B., Meller, R.D., Ballot, E.: Towards a physical internet: the impact on logistics facilities and material handling systems design and innovation. In: Progress in Material Handling Research, pp. 305–327 (2010)
12.
Raggl, S., Fechter, J., Beham, A.: A dynamic multicommodity network flow problem for logistic networks (2015)
13.
Sarraj, R., Ballot, E., Pan, S., Hakimi, D., Montreuil, B.: Interconnected logistic networks and protocols: simulation-based efficiency assessment. Int. J. Prod. Res.
52(11), 3185–3208 (2014)
CrossRef
14.
Toth, P., Vigo, D.: Vehicle Routing: Problems, Methods, and Applications. SIAM, Philadelphia (2014)
CrossRefMATH
15.
Van Belle, J., Valckenaers, P., Cattrysse, D.: Cross-docking: State of the art. Omega
40(6), 827–846 (2012)
CrossRef
16.
Van Lon, R.R., Holvoet, T., Vanden Berghe, G., Wenseleers, T., Branke, J.: Evolutionary synthesis of multi-agent systems for dynamic dial-a-ride problems. In: Proceedings of the 14th Annual Conference Companion on Genetic and Evolutionary Computation, pp. 331–336. ACM (2012)
17.
Vonolfen, S., Beham, A., Kommenda, M., Affenzeller, M.: Structural synthesis of dispatching rules for dynamic dial-a-ride problems. In: Moreno-Díaz, R., Pichler, F., Quesada-Arencibia, A. (eds.) EUROCAST 2013. LNCS, vol. 8111, pp. 276–283. Springer, Heidelberg (2013).
https://doi.org/10.1007/978-3-642-53856-8_35CrossRef
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