Yard storage strategies, dwell time reduction, and performance outcomes in an emerging automated maritime terminal

This research investigates how container dwell time affects the throughput and rehandling productivity at maritime terminals with focus on Lekki Freeport Terminal (LFT) - an emerging automated maritime hub in Nigeria. A deterministic slot-based rehandling structure is first established to characterize the vertical inefficiency embedded in dense stacking configurations, after which Monte Carlo Simulation is applied to capture uncertainty in container retrieval. Results show strong statistical consistency of the simulation, with the expected number of rehandles converging tightly to a theoretical mean of 2.00 as sample size increases. Scenario analysis reveals a nonlinear relationship between average stack height and rehandling intensity: expected rehandles rise from 0 at a stack height of 1.00 to 1.22 at 2.29 tiers. When heterogeneous retrieval behavior is introduced, expected rehandles increase substantially, exceeding 1.9 at low stack heights and remaining significantly higher than under equal-probability assumptions. These findings demonstrate that ignoring demand heterogeneity leads to systematic underestimation of congestion and handling costs. The study provides quantitative evidence to support stochastic, data-driven yard planning as a basis for improving operational efficiency and economic sustainability in emerging container terminals.