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Item type:Publication, Access status: without files , Logistic operating curves for closed queueing systems: Enhancing container terminal productivity through shared queuesContainer terminals are vital nodes in global supply chains, linking maritime and land transport. Terminal operators face the critical challenge of balancing vessel handling times and operational costs – a conflict of objectives. Building on our previous work that introduced an engineering-oriented approach using Logistic Operating Curves and an extended Kingman approximation for ship-to-shore crane productivity under fixed vehicle allocations, this paper advances the model to accommodate shared vehicle queues. In such configurations, terminal trucks serve multiple ship-to-shore cranes from a common pool, preserving the closed queueing system characteristics inherent to terminal operations.Publicationtype: Conference Paper38 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Assignment of orders in horizontal transport at sea-port container terminals(Springer Nature Switzerland, 2026-07-09); ; ; ; Quay cranes (QCs) represent the primary operational bottleneck at seaport container terminals due to their high capital intensity and role as critical nodes in global supply chains. Their productivity is strictly dependent on the efficient coordination of horizontal transport, specifically the assignment of transport orders to terminal trucks (TTs). While many terminals still rely on fixed TT-to-QC assignments, this approach often lacks the flexibility to handle disruptions and fluctuating workloads. This paper investigates the potential of a flexible, multi-criteria assignment procedure – considering work-in-process, travel distances, and QC waiting times – compared to traditional fixed assignments. The performance is evaluated using Logistic Operating Curves (LOCs), which map QC productivity against the number of deployed TTs. The results demonstrate that flexible assignment significantly outperforms fixed assignment in underload scenarios (low TT availability or high travel speeds), showing productivity gains of up to 17.85% during vehicle disruptions. However, this advantage diminishes as transport capacity increases. In high-utilization overload zones, the flexible method falls slightly below fixed assignment performance. This discrepancy is attributed to the timing of order assignment; making decisions when a previous task is completed, rather than at the last possible second, limits the system’s ability to react to real-time fluctuations. The study concludes that flexible assignment increases robustness during transport shortages, but achieving theoretical productivity benchmarks requires shifting toward late-assignment strategies.Publicationtype: Conference Paper79 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Access status: without files , Modelling of logistics objectives at the sea side of container terminalsIn the context of the expanding global economy, the significance of transport chains has been increasingly recognized, with container terminals assuming a pivotal role within these networks. The competitive environment has led to pressure on these terminals, giving rise to a conflict of logistical objectives such as short vessel handling times and minimized handling costs. Previous attempts to address this issue, including simulation studies and deterministic mathematical models, have yet to be effectively implemented in practical settings due to their sensitivity to parameters and inherent complexity. This study proposes a novel engineering-centred approach utilizing Logistic Operating Curves to model terminal objectives, with a particular emphasis on quayside operations such as container handling by ship-to-shore cranes and terminal trucks. The paper explores the derivation of ideal and real Logistic Operating Curves for ship-to-shore cranes. Therefore, the well-known Kingman equation is extended to map the special characteristics of a closed queueing system. The simulation experiments conducted demonstrate that the proposed model provides sufficient accuracy in predicting mean productivities. The study concludes that the Logistic Operating Curves framework serves as an effective, understandable and adaptable method for improving terminal operations and highlights areas for further research.Publicationtype: Conference Paper123