Managing empty-container movements is one of the most challenging logistics problems in the shipping field. With the growth of global trade imbalance, the repositioning process has become necessary, immediately after emptying a container. The main contribution of this research paper is to enrich the most frequently used methods, models, and applications in the literature, for relaxing the empty-container-repositioning problem. The article presents practices that vary between organizational policies, technical solutions, and modelling applications. A review of optimization models has been used for comparisons, based on specified criteria, such as the time frame, inputs, outputs, scale of the project, and value. Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) was applied through the online database Web of Science (WOS). It gives a comprehensive description of all the relevant published documents. On the basis of conducting a brief systematic review, future research opportunities have been determined, considering the emerging phenomena in container transport chains.

Due to an ever-increasing movement of containers across the globe in line with the economic boom, the trade imbalance and issues related to empty containers have become inevitable. Empty containers accumulated at specific ports cannot only generate profit but also increase the environmental footprint. This research proposes a Maritime Empty Container Reposition Modelling Framework by integrating the agent-based modelling (ABM) paradigm to model the global movements of empty containers. An agent-based maritime logistic empty container redistribution model was developed to help minimize the total relevant costs for empty container movement in the planning horizon. In the system, ports, shipping companies, customers, and empty containers were identified as critical agents. Using simulated annealing (SA), shipping line agents were able to optimise empty container repositioning to determine the best sequence for moving containers. The model was applied to the Asia–Middle East region to simulate global empty containers repositioning in the region. The results comparison shows that the proposed optimised empty container repositioning framework can significantly reduce the shipping line’s costs and make full use of empty containers.

Inefficient inland repositioning of empty containers between depots remains a persistent challenge in container logistics, contributing significantly to unnecessary truck movements, elevated operational costs, and increased CO₂ emissions. Acknowledging the importance of this problem, a large amount of relevant literature has appeared. The objective of this paper is to track the empty container flow between ports, empty depots, inland terminals, and customer premises. Additionally, it aims to simulate and assess CO₂ emissions, capturing the dynamic interactions between different agents. In this study, agent-based modeling (ABM) was proposed to simulate the empty container movements with an emphasis on inland transportation. ABM is an emerging approach that is increasingly used to simulate complex economic systems and artificial market behaviours. NetLogo was used to incorporate real-world geographic data and quantify CO₂ emissions based on truckload status and to evaluate the other operational aspects. Behavior Space was also utilized to systematically conduct multiple simulation experiments, varying parameters to analyze different scenarios. The results of the study show that customer demand frequency plays a crucial role in system efficiency, affecting container availability and logistical tension.