Scheduling truck arrivals for efficient container flow management in port logistics

Area of Science:

• Operations Research
• Logistics Management
• Transportation Engineering

Background:

• Container terminal operations face significant challenges from truck arrival congestion.
• Congestion impacts port efficiency, logistics, and the surrounding environment.
• Efficient management of truck queues and internal routing is essential for optimal port functioning.

Purpose of the Study:

• To develop a mathematical model for optimizing truck routes and schedules at container terminals.
• To address congestion both outside and inside port gates.
• To enhance overall port process efficiency through improved truck management.

Main Methods:

• Formulation of a mixed-integer linear programming (MILP) model.
• Inclusion of port features: external parking, multiple gates, internal roadways, and docks.
• Development of a rolling horizon heuristic for complex instances.

Main Results:

• The MILP model provides optimal truck routes and schedules.
• The heuristic method offers solutions for computationally intractable problems.
• Simulated evaluations using real-world data validate the methods' effectiveness.

Conclusions:

• Optimized truck management significantly improves container terminal efficiency.
• The proposed MILP formulation and heuristic are effective tools for port logistics.
• This approach contributes to reduced congestion and better environmental outcomes in port operations.