Models and methods for container port congestion mitigation

Abstract

Driven by the development of global trade, demand for containerized cargo freight has been growing over the years, leading to frequent vessel calls at major container ports around the world. As a consequence, traffic congestion has increasingly become a burden in the busiest container ports. High levels of congestion impede vessel service, causing long waiting times and severe vessel delays. This thesis studies two optimization problems that aim at mitigating container port congestion caused by the traffic of vessels. The first problem is a berth allocation problem in which the vessels are classified into deep-sea vessels and feeders. While the arrival times and service times of deep-sea vessels are known to the port operator when berth plans are being devised, the service times of feeders are usually uncertain due to lack of data interchange between the port operator and the feeder operators. The uncertainty of feeders' service times can incur long waiting lines and severe port congestion if the berth plans are poorly devised. To alleviate port congestion and achieve satisfactory vessel service, we allocate berth space to deep-sea vessels and schedule the arrivals of feeders so that the congestion caused by the feeders is under control, while the departure tardiness of deep-sea vessels and the schedule displacements of feeders are minimized. We develop a stochastic optimization model for this problem, and propose a three-phase simulation optimization method, in which the simulation budget is wisely allocated to the solutions explored. The second problem aims at scheduling the vessel traffic in the port waters by managing the utilization of the navigation channel and the anchorage areas. Navigation channels are fairways for vessels to travel in and out of the terminal basin of a container port. The capacity of a navigation channel is restricted by the number of traffic lanes and safety clearance of vessels, and the availability of a navigation channel is usually affected by tides. The limited capacity and availability of a navigation channel could lead to congestion in the terminal basin. When the navigation channels run out of capacity, the anchorage areas in the terminal basin could serve as a buffer. We develop a mathematical model that simultaneously optimizes the navigation channel traffic and anchorage area utilization. We analyze the complexity of the model and propose a Lagrangian relaxation heuristic in which the relaxed problem is decomposed into two asymmetric assignment problems. We evaluate the computational performance of the proposed solution methods using test instances generated based on the operational data of the Yangshan Deep-water Port in Shanghai. Computational results show that the proposed solution methods achieve satisfactory performance within reasonable computation time and outperform benchmark methods in terms of congestion mitigation and vessel service enhancement.