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<p>This paper addresses the optimization of truck dispatching for bulk unloading operations at the Port of Itaqui, a critical logistics hub in Brazil. Traditional manual dispatch processes often result in inefficiencies such as congestion, delays, and elevated emissions. To mitigate these issues, a Mixed-Integer Linear Programming model was developed to minimize queue imbalances, waiting times, and CO<sub>2</sub> emissions while maintaining operational efficiency. The model was compared against a benchmark algorithm representing current operator practices in a discrete-event simulator, reducing truck queues and waiting times by up to 65% in the Primary Area without extending total unloading time or overall truck emissions. Although validated in a simulation environment, these results provide a preliminary basis for real-world deployment and further investigation into truck flow automation in bulk port logistics.</p>

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Responsive Mathematical Modeling and Discrete-Event Simulation for Optimizing Truck Dispatch in Bulk Port Unloading Operations

  • 期刊论文

  • 出版模式：

    开放获取

  • 发表日期：

    2026年6月1日

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  • Victor José Beltrão Almajano Martinez,
  • Carlos Eduardo Veras Gomes,
  • João Augusto F. N. Carvalho,
  • Joana K. A. Silva,
  • João Dallyson Sousa Almeida,
  • Geraldo Braz Junior,
  • Tiago Bonini Borchatt,
  • Francisco Glaubos Nunes Clímaco

摘要

This paper addresses the optimization of truck dispatching for bulk unloading operations at the Port of Itaqui, a critical logistics hub in Brazil. Traditional manual dispatch processes often result in inefficiencies such as congestion, delays, and elevated emissions. To mitigate these issues, a Mixed-Integer Linear Programming model was developed to minimize queue imbalances, waiting times, and CO2 emissions while maintaining operational efficiency. The model was compared against a benchmark algorithm representing current operator practices in a discrete-event simulator, reducing truck queues and waiting times by up to 65% in the Primary Area without extending total unloading time or overall truck emissions. Although validated in a simulation environment, these results provide a preliminary basis for real-world deployment and further investigation into truck flow automation in bulk port logistics.