Improvement of Container Terminal Productivity with Knowledge about Future Transport Modes: A Theoretical Agent-Based Modelling Approach

Abstract

Despite all the achievements in improving container terminal performance in terms of equipment and container stacking systems (CSS), terminal operators are still facing several challenges. One of these challenges is the lack of information about further transportation modes of the container, which leads to extra movements of the container inside the stacking area. Hence, we aimed to examine factors that affect container handling processes and to evaluate a container terminal’s overall equipment effectiveness. This study used data from a container terminal at the Port of Antwerp, Belgium. An agent-based model was developed based on a block-stacking strategy to investigate two scenarios: (1) having information about further transportation modes and (2) a base scenario. The Overall Equipment Effectiveness Index (OEE) was also adopted to evaluate the container terminal’s effectiveness in both scenarios. Results showed that having information on further transportation mode significantly increased the container outflow, and the OEE index improved compared to the base scenario’s results. Therefore, we recommend an integrated data-sharing system where all the stakeholders can share their information with no fear of losing their market share.

Lessons from Reality on Automated Container Terminals: What Can Be Expected from Future Technological Developments?

“…To address this, newer telecommunication technologies, for example 5G, could provide more robust platforms to ensure such industrial applications. Another internal factor limiting productivity is the container stacking problem and the lack of information that generate re-stowage and unproductive moves (32). As Voß et al comment, the optimization problem is complex, as a container terminal is a dynamic system (33).…”

“…Another internal factor limiting productivity is the container stacking problem and the lack of information that generate re-stowage and unproductive moves ( 32 ). As Voß et al comment, the optimization problem is complex, as a container terminal is a dynamic system ( 33 ).…”

Utilizing Amphibious AGVs to Optimize Container Transshipment for Deep Sea and Hinterland Operations

“…In that case, these agents have their functions, such as loading, unloading, and container inventory management, while they have separate interactive functions, such as loading and then leaving. ABM has found its relevance in various areas of container shipping, namely in frameworks for reducing congestion (Shobayo and Van Hassel, 2019), container terminal productivity (Mazloumi and van Hassel, 2021), and most importantly, in both inter-terminal transport (Iqbal, 2015) and interland (Feng et al, 2015).…”

Empirical Performance Measurement of Cargo Handling Equipment in Vietnam Container Terminals

“…However, the study did not measure each piece of equipment as well as group equipment in the frontline. Likewise, Mazloumi and van Hassel [23] calculated OEE for the general operation of the port, which mentioned the influence of groups of loading and unloading equipment, such as shore cranes, yard cranes, trucks, and so on. However, the OEE for each equipment and group of equipment of CHE was not taken into account.…”