Rule-based dynamic container stacking to optimize yard operations at port terminals

Abstract

The global container volume has been increasing over the past two decades due to the growth in seaborne trade due to rapidly globalizing supply chains. Simultaneously, container terminals tend to either expand their capacity, optimize the existing operations or consider a combination of both to cater to the growing demand. This study focuses on the Container Stacking Problem (CSP) which determines the exact yard locations for incoming containers. There are two approaches in CSP: Static Container Stacking (SCS) and Dynamic Container Stacking (DCS). This study aims to investigate the impact of DCS (real-time yard planning) approach through three objectives: (i) establish a DCS model to deal with a higher degree of uncertainty in container terminals, (ii) reduce container handling costs by minimizing yard crane travelling distance, horizontal-transport vehicle travelling distances and optimizing workload distribution of yard blocks, and (iii) analyze the performance of DCS and SCS to identify the best approach. The paper introduces a Rule-Based Dynamic Container Stacking (RBDCS) model which contains a three-step methodology. The developed RBDCS model determines yard locations in real-time at the point of container arrival while minimizing the container handling cost and considering uncertainty. The developed model has been validated for discharging operations from the data which were collected at a major Asian transshipment port. Computational test results reveal that container handling costs can be significantly reduced through implementing the developed model. Finally, this study emphasizes that DCS is ideally applicable for transshipment-oriented terminals while the SCS approach is ideally applicable for gateway terminals.