Container slot booking cancellation could cause a loss of revenue for shipping companies, which has been an inevitable challenge for the container liner shipping industry. To counter this issue, a thesis by Dr Zhuo Hui, a Scientist from the System Science department at A*STAR’s Institute of High Performance Computing (IHPC) investigated two correlated problems: the analysis of slot booking cancellation pattern, and the strategies of capacity control to remedy the revenue loss incurred by the uncertain slot demand. 

Slot booking cancellation and the resulted uncertainty of slot demand motivate the ship capacity control problem. Four subproblems were addressed relating to the two key problems: 

The first subproblem aims to discover the pattern of slot cancellation behaviour using data mining methods, which lays a logical foundation for the second subproblem of estimating cancellation probability. Considering the influential factors of cancellation behaviour in the first subproblem, the cancellation probability estimation problem aims to forecast the probability of slot booking cancellation during the slot booking period. A data-driven model is developed based on a time-to-event analysis method and a frailty term to consider the regionality of shipping market. The result of the case study shows that the model’s performance on forecasting cancellation probability is satisfying. Additionally, this thesis provides an effective index to rank the cancellation probability in different market regions. 

The tactical slot allocation problem seeks the optimal slot allocation plan for different segments of container shipping demands in a shipping network. Considering the uncertainty incurred by the slot booking and cancellation, the demand for container slot is assumed to be stochastic with known fundamental statistical descriptive but unknown distribution. A distributionally robust optimisation model is established to handle the uncertain container slot demand to maximise the expected revenue. The capacity control problem over the slot booking period is an operational level problem considering both the cancellation of slot booking and the tactical slot allocation plan determined in the third subproblem. This problem determines a policy for a shipping company to accept/reject a slot booking request from shippers. The result of the numerical example shows that the capacity control methods developed by this thesis could guarantee a high revenue in the context of uncertain demand incurred by slot booking cancellation, and outperforms the conventional policy adopted in practice.

The methodology developed in this study could serve as an efficient tool for container liner shipping companies to maximise their revenue under the uncertainty of slot booking and cancellation. The data-driven optimisation theory proposed by this thesis could also promote the digitisation and intelligence of shipping management.

“I feel truly honoured that my work has been recognised. I would like to thank my Ph.D. supervisor - Prof. Meng Qiang for his strong support and guidance during my Ph.D. study. I also feel inspired to contribute my knowledge and skills to the maritime research in IHPC”, says Dr Zhao. 

The 8th Triennial MEL PhD Competition 2019-2022: Results.

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