In recent literature, it is indicated that freight transportation via trucks is still insufficient in terms of efficiency and sustainability. Reasons for such inefficiency are poor utilization of capacities (drivers, trucks, containers etc.), high shares of empty mileage, as well as lacking flexibility when responding to an increasing market volatility. It is assumed that future transport systems will have to deal with higher urgencies and with smaller lot sizes. In course of this, the assignment of transport orders will be characterized by increasing spontaneity and an uncertain planning environment for logistics service providers.
Thus, the objective of this paper is to present a conceptual model that combines a dynamical price prediction model and an approach for the dynamical assignment of freight flows through a network of hubs. Due to a constantly changing environment (e.g. demands, capacities, and/or prices), freight assignment will be updated continuously. As a result, the operational freight flow will evolve over time and choose the most cost-efficient route through the network by dynamically bundling and unbundling itself.
After a brief introduction on recent Physical Internet (PI) research, this paper will give a description of the proposed model, for a continuous and dynamic freight flow assignment. Eventually, we will discuss the results and conclude with the implications on our research.
Multiple different attributes are important in the container-to-mode assignment in a transportation network. This paper proposes an interactive multi-objective optimisation approach for planners of those transportation networks. This approach offers a range of solutions according to her/his preferences, and offers the opportunity to seek for new ones if the planner is not satisfied with the solutions found so far.
In logistic problems, an Integral Multi-Commodity Network Design Problem
on a time-space network is often used to model the problem of routing
transportation means and assigning freight units to those means. In
Physical Internet and Synchromodal networks an interactive planning
approach is preferable, meaning that calculation times of a single
planning step should be short. In this paper we provide finding ways to
reduce the number of variables in the problem formulation, that are
effective at reducing the computation time for ILP-based solution
methods.
Environmental concerns raise the need for more efficiency and sustainability in the freight transportation sector. For this purpose, the Physical Internet is introduced, which aims to connect logistics networks into one hyperconnected supernetwork. To transport freight over such an integrated network, the innovative concept of synchromodality is presented. Synchromodality is defined by the usage of multiple modalities when planning shipments, where real-time switching between transportation modes is possible. In this work, we introduce a synchromodal planning model that constructs optimal transportation routes in a multimodal network with stochastic transit times, formulated as a mixed-integer linear programming problem. To cope with the transit time stochasticity, transportation routes are adapted in accordance to real-time information about the transit time outcome. In a numerical study, we demonstrate the potential advantages that synchromodality entails in terms of costs, service quality and environmental impact.
Tomas Ambra, An Caris and Cathy Macharis
Transparency and information exchange are important parts of
synchromodality that contribute to better overview of options when
tackling delays, dynamic switching, and handling of unexpected events
that affect delivery lead-times and costs. The most challenging aspect
when making decisions in a complex adaptive dynamic system, is the
ever-changing environment as we introduce more flexibility which may
lead to more unpredictable outcomes. This paper presents 2 simple
illustrative cases to asses different transparency levels and the
adaptive behavior of assets; 1) a static case where assets do not have
the ability to respond proactively to disruptive events, and 2) a
dynamic case where assets have the ability to query their environmental
context and exchange information. The severity of the events is captured
by probability distribution functions by deploying Monte Carlo
simulations to showcase the potential benefits of the Digital Twin
concept in a synchromodal context. The links between current Digital
Twin applications and synchromodal transport are discussed in order to
spark a new wave of reducing uncertainties in dynamic environments.
Lastly, the paper sheds more light on how to connect closed virtual
simulations with the real physical system.
We provide a method to obtain a User Equilibrium in a transportation network, in which we transport containers for multiple agents. The User Equilibrium solution is defined as the solution wherein each agent can travel via their cheapest paths possible, and no agent is harmed by the route choice of other agents. The underlying model used is the Space Time Network (STN), in which the travel time of modalities is fixed and independent of the occupancy of the network. The System Optimal solution is the solution in which the total costs of the network are minimised. An approach is presented to find a toll scheme to create a User Equilibrium solution in this tolled STN, while maintaining the System Optimal solution of the initial STN.