Slot Optimization Disruption Management Model And Algorithm Of Import Containers In Container Yard

One of the most important objectives of operations optimization in container terminal yard is to reduce the reshuffle ratio, which is an important way for slot optimization during picking up import containers. Reducing reshuffle ratio could directly reduce operating costs of container yard, and improve the competitive strength of the port. With the sharp increase of container throughput, most ports are limitations due to the land area and yard operations required, so they take a multi-layer stacking measure to adapt to these limitations, but it may create many invalid reshuffle and complex operational problems. Also, it is affected by many external uncertain factors, such as the uncertainty of customer picking-up time, which also create lots of reshuffle, bring greater influence to the yard operation plan and increase the operation costs. Therefore, taking slot optimization research, optimizing reshuffle ratio has important significance to enhance the efficiency of container transport, stacking effectiveness, as well as profit, service levels, modern management of the port.For the problem of slot optimization, we firstly analyze the relevant factors of reshuffle. According to the characteristics of customers picking-up time, establish picking up order model under stochastic and uncertain condition, considering the hard solving characteristic of the model, develop a fast heuristic algorithm and test the performance of the algorithm, simulation experiments results show that the heuristic algorithms can meet the solving accuracy and real-time requirements. Then, discuss the solution of expected number of reshuffle estimate; propose a heuristic algorithm based on least-two-time-reshuffle-estimate rule for slot optimization of import containers. Simulation experiments results show that the accuracy of proposed algorithm can be15%more than OH and IH algorithm while solving larger-scale problem.For the influence of disruption event to operation plan of picking-up containers, we firstly analyze the relevant disruption factors of reshuffle and measure these factors, on this basis, then, establish disruption management model to adjust the original operation plan and minimize the disturbance. Finally, a comparative analysis of proposed algorithm compare with rescheduling algorithm by simulation experiments, the experimental results show that the the disruption management model calculated reshuffle is slightly higher than rescheduling algorithm, but less disturbance to the original operating plan, and the caclution time is acceptable and could get satisfactory solution.