Operating parcel transshipment terminals: a combined simulation and optimization approach


Parcel transshipment terminals are complex systems that consist of automatic conveyor networks and manual handling activities. Therefore, using discrete-event simulation to evaluate a terminal seems obvious and is often used in the literature. On the other hand, mathematical optimization represents a powerful method that has been successfully used to solve a wide range of logistical problems. Simulation allows for modeling logistics systems with almost unlimited complexity very close to reality, but finding the best system configuration is difficult and time-consuming. In contrast, mathematical optimization has the ability to make complex decisions and find (near) optimal solutions. Real-world logistic systems, however, can only be solved on a lower level of detail without stochastic behaviors. In this article, we present a modeling framework for the operational planning of a transshipment terminal that closely links both methods in order to make use of their complementary advantages. Thus, we are able to handle a large number of decisions, such as (un)loading dock and sorting destination assignments, and consider complex automatic sorting systems as well as manual handling activities with stochastic elements. The approach is evaluated on the example of a parcel transshipment terminal using three different input data scenarios.

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The presented results are part of the work from the research project “Development of a combined approach that links discrete mathematical optimization and stochastic simulation for planning and operating logistics nodes (applied to transshipment terminals in the parcel delivery industry)” funded by the Deutsche Forschungsgemeinschaft (DFG—German Research Foundation).

Authors’ contribution

Mathematical optimization and discrete-event simulation include two of the most powerful OR techniques. However, these two techniques are mainly used separately. Our article proposes a combined framework that closely links both methods in order to make use of their complementary advantages. On the one hand, optimization allows modeling and solving complex problems to find a near optimal system configuration. On the other hand, the advantage of simulation is that it allows us to study phenomena close to reality that are difficult or too complex to describe and solve analytically. Therefore, our contribution is to bridge knowledge to enable a joint usage of both methods in a combined approach.

Our article not only aims as a valuable contribution to bridging the currently existing scientific and methodological gap at the interface between optimization and simulation, but we also intent to show the concrete practical benefits of our approach for operating parcel transshipment terminal. By using a practical application example, our target is to proof that a combined approach is applicable for practical operational planning as well as to show that the combined use of simulation and optimization ultimately leads to better results than one of two methods could achieve on their own.

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Correspondence to Uwe Clausen.

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Clausen, U., Diekmann, D., Pöting, M. et al. Operating parcel transshipment terminals: a combined simulation and optimization approach. J Simulation 11, 2–10 (2017). https://doi.org/10.1057/s41273-016-0032-y

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  • discrete-event simulation
  • optimization
  • parcel transshipment operations