Concepting Freight Holding Problems for Platoons in Physical Internet Systems

Abstract

For the sustainability of future logistics systems, Physical Internet is one of the most determined idea. Initial solutions and ideas exist, but the development in this area is far from complete. In our opinion, vehicle technology trends such as interconnected, autonomous vehicles and the platooning system are an important opportunity for the development of logistics network. This research aims to investigate how these new types of processes can be modelled using the results of a freight holding problem. The article surveys the possibility of reconfiguration of the platoons in the Physical Internet system by creating a virtual transfer point.

Optimization of a physical internet based supply chain using reinforcement learning

“…We assume that all HDVs interact and communicate with each other and the hubs are open and accessible to all PI users. The presented model extends the transportation model outlined in the article [24]. As stated in the article [24], the objective is to optimize the shipping tasks performed by platoons between predefined hubs.…”

“…The presented model extends the transportation model outlined in the article [24]. As stated in the article [24], the objective is to optimize the shipping tasks performed by platoons between predefined hubs. This requires a virtual hub to provide a common meeting point for the selected platoon.…”

“…Fig.2Theoretical model. Theoretical model for virtual transfer point optimization in Physical Internet network (based on[24])…”

Physical Internet: First results and next challenges

“…Osmólski et al (2019) present dedicated PI solutions to logistic processes such as modular transport units and real‐time planning and information exchange, as well as properly designed communication infrastructure. Puskás et al (2019) explore the use of interconnected autonomous vehicles and platooning systems for modeling an existing freight holding problem in a PI system, leading to a dynamic real‐time reconfiguration for platoons. Qiao et al (2019) introduce a PI‐based optimization model that can be used for multi‐leg dynamic pricing and request selection within the LTL industry.…”

“…Lemmens et al (2019) demonstrate, using a simulation study, that synchronized intermodality (employing multiple modes in a flexible dynamic way) can induce a modal shift toward low carbon transport modes that are useful in PI. Puskás et al (2019) suggest a key part of the Physical Internet is the need for interconnected autonomous vehicles that utilize a platooning system, and they determined that a reinforcement learning‐based model performs better for high incoming vehicle numbers and a heuristics‐based model performs better for low vehicle numbers.…”