Kim and Park [99] focus on export containers and show a dynamic space allocation
method in order to utilize storage space efficiently and to increase efficiency of
loading operations. A basic MIP-model is formulated. Two heuristic algorithms – amyopic (least-duration-of-stay) rule and a sub-gradient optimization technique –
are compared in computational experiments. Results are in ‘almost the same level
of objective values’, but the decision rule is much faster. Effects of changing values
of several model parameters are also analyzed.
Zhang et al. [211] study the storage space allocation problem in a complex terminal
yard (with inbound, outbound and transit containers mixed). In each planning
period of a rolling-horizon approach the problem is decomposed into two levels
and mathematical models. The workload among blocks is balanced at the first level.
The total number of containers associated with each vessel and allocated to each
block is a result of the second step which minimizes the total distance to transport
containers between blocks and vessels. Numerical experiments show significant
reduction of workload imbalances and, therefore, possible bottlenecks