A two-stage stochastic programming for single yard crane scheduling with uncertain release times of retrieval tasks

Nowadays maritime transportation has become the mainstream of the global logistics, and the operational efficiency of container terminals plays a critical role in maritime transportation. As one of the most important terminal operational issues, yard crane scheduling that handles both storage and retrieval tasks has caught a lot of interest. However, the uncertainty on the release times of retrieval tasks, as one common phenomenon in daily operations, has been ignored in the literature. This paper investigates single yard crane scheduling to minimise the expected total tardiness of tasks, and focus on the case with uncertain release times of retrieval tasks. A two-stage stochastic programming model is proposed, and the sample average approximation (SAA) approach is applied to solve small instances of the problem. For large-scale instances, a genetic algorithm (GA) and a rule-based heuristic are developed. To evaluate the performances of the solution methods, numerical experiments with 300 instances are implemented. Computational results show that the rule-based heuristic outperforms both GA and SAA in terms of solution quality and running time.

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