We propose a process algebra called “the synchronized ambient calculus (SAC)”, which is an extension of the ambient calculus (AC). The processes of AC have a layered structure of ambients that enable us to describe not only mobile processes but also real entities such as networks, factories and freight systems in which synchronization between objects is crucial. For example, a container must be brought out from a container yard just after the container ship reached the terminal. While such a protocol can be described using the primitives (in, out, open) of AC, the protocol is easily corrupted due to the phenomenon called “grave interference”, which led us to design SAC. The following advantages for using SAC are that we can describe synchronized actions of objects without grave interference and expressions for such synchronized actions can be simpler than using AC. We give an example of SAC processes for stacking containers in constrained shipping order, e.g., in ascending order, the execution sequences of which can be used to improve the efficiency of the reinforcement learning method we are currently developing.

This paper proposes a cargo transport simulator based on the Ambient Calculus (AC) for efficient trucking planning. While the decline of transportation capacity is a part of the so-called “2024 issue” that the Japanese logistics industry is currently facing, the loading rate of trucks for the intra-regional medium-lot cargo transportation in particular remains low at about 40% because of inefficient truck operations, such as individual delivery planning even among neighboring distribution centers. Various dispatch planning systems are being used to improve loading rates and cope with the decline in transportation capacity. However, despite these efforts, the loading rate remains low. This indicates that medium-lot cargo transportation within a regional block is an area where efficiency is particularly difficult to improve. To develop efficient transportation planning, the on-site operational model needs to be accurately described. This research takes advantage of the property of process algebra that can explicitly express nondeterminism. The cargo transport simulator proposed in this paper makes trucking plans by nondeterministically combining deliveries that satisfy conditions such as distance, direction, weight, and type of cargo. For this purpose, we propose a syntactic extension of AC suitable for modeling trucking, and implement a delivery plan presentation function using the processing system of the language.