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Container ports are critical components of global port and shipping supply chain (PSSC) systems. Their handling operation resiliencies can affect their performance, along with those of the overall port and shipping supply chain. According to the characteristics of the container handling operations, this study establishes a modeling paradigm for quantifying the resilience of handling chain system (HCS) in container ports. Considering the nonnegative arrive rate and the container handling completion rate, with the upper limit in real container port environments, nonlinear links have been added into the model of the HCS. The resilience of the HCS was analyzed according to the different pole distributions of unsatisfied freight requirement transfer function. Simulation results show that the upper limit of the container handling completion rate has a significant impact on the resilience of the HCS. The contributions herein demonstrate a starting point in the development of a quantitative resilience decision making framework and mitigating the negative impacts for port authorities and other players in the PSSC.

Container throughput in Shanghai port has been continually increasing, with severe congestion impacts. The effectiveness and comprehensiveness of governance policies are increasingly important. This study proposes a conceptual framework and simulation of congestion governance measures and their effectiveness on congestion control in a data-driven case study for Shanghai port. The contributions herein serve as a starting point in the identification of four alternative congestion governance options (Increasing the transport infrastructure, Multimodal transport, Smart strategy, and Interconnection), and explore dynamic interactions among them. The design of this study is to firstly develop a container port congestion evaluation model to measure the governance effect; secondly to undertake the triangle analysis in the dynamic system balance: demand of hinterland transport, container port congestion, and container port congestion governance; thirdly to describe four congestion governance options with a detailed description of feedback loops generated by the system dynamics model; finally to propose a policy framework aiming at the advantages and disadvantages of these four options. This study function as stepping stones towards the revealing of the biggest challenge in effective mitigation of port congestion systems by being considered not just a hardware issue (option 1) but more importantly organizational issues (options 2~4). It should be a process of coordination and optimization among 4 options.

Nonlinearities in a container port handling chain include mainly nonnegative arrive rate of container cargoes, limited container handling completion rate, and nonnegative unsatisfied freight requirement constraints. The nonlinearity influences the operation resources availability and consequently the planned container port handling strategies. Developments presented in this work are devoted to a novel design of sliding mode control with low-pass filter (SMC-LPF) to nonlinear handling chain system (HCS) in container ports. The SMC-LPF can effectively reduce unsatisfied freight requirement of the HCS and make chattering decrease significantly. To illustrate the effectiveness and accuracy of the proposed SMC-LPF, an application to a real container port in China is outlined. The performances of the SMC-LPF for the nonlinear HCS in container ports outperform those of the traditional method, particle swarm optimization algorithm, and slide mode control under simulations with a unit step signal and a sinusoidal signal with offset as the freight requirements. The contributions herein demonstrate the proposed control strategy in weakening chattering, reducing the unsatisfied freight requirements to 0 as close as possible in the HCS, maximizing the operation resilience and robustness of port and shipping supply chain against parametric perturbation, external disturbances, and fluctuant handling abilities.

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