Design and development of in‐the‐loop test and evaluation platform for space allocation at shipping container terminal

As a vital component in the shipping industry, coastal container terminals must be developed in a sustainable manner. The container receiving process is a crucial aspect of container loading and transportation and is the cornerstone of container terminal operations. This process is characterized by its discrete random events. To model this process, the testbed was designed and developed using a Hierarchical Generalized Stochastic Petri Net (HGSPN) workflow engine to drive the data and simulate the container receiving process through the interplay of resources and changes. Random indexing was utilized to mimic the discrete randomness of the operations. The performance of the container receiving process was validated and evaluated through the construction of an operational energy and efficiency‐focused container receiving evaluation model. Results showed that the intelligent container receiving system, tested on the in‐loop platform, can effectively evaluate the strengths and weaknesses of container receiving, leading to continuous improvement of the system and demonstrating its significant practical value. The article utilizes the HGSPN workflow engine to perform data‐driven simulation of the container receiving process, and constructs an evaluation model with the goal of optimizing operational energy consumption and efficiency by simulating the discrete randomness in the container receiving process through random indexing. The conclusion shows that the in‐the‐loop test and evaluation platform can effectively evaluate intelligent algorithms and promote algorithm optimization.