<![CDATA[Efficient gate operations at marine container terminals (MCTs) are critical for reducing truck waiting times, minimizing congestion, and improving port economic performance. Purpose – This study develops a stochastic queuing-based optimization framework using M/Eₖ/S multi-server models to represent truck arrivals and gate service processes. Statistical goodness-of-fit tests confirmed that truck inter-arrival times follow an exponential distribution, while service times align with an Erlang distribution. Methodology – The methodology adopts a queueing–optimization framework to evaluate and improve marine container terminal (MCT) gate operations by minimizing the combined costs incurred by terminal operators and trucking companies. The gate system is characterized by two principal cost components: gate operating costs borne by the service provider and truck waiting costs incurred by users. Findings – Optimization results indicate that implementing the model reduced average truck waiting times from 9.8 minutes to 6.3 minutes and decreased total daily gate costs by approximately 23% across operating hours. The optimal number of gate lanes varied with traffic density, demonstrating the importance of adaptive lane allocation. Originality – Policy implications highlight investment in predictive analytics, dynamic scheduling, and resource allocation to enhance port efficiency, throughput, and economic competitiveness ]]>
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