Optimization of resource allocation for rail container terminals based on internet of things technology

In this paper, an improved adaptive clonal immune algorithm is presented to solve an extended space allocation optimization problem in a rail container terminal. The space allocation optimization problem is defined as two parts: the temporary allocation of the import/export containers to the bays at each time period with the aim to balance the workload between blocks and based on the workload of each block determined in the first model with the aim is to minimize the total distribution distance between arrival-departure tracks and the storage blocks. The performance of the allocation models and proposed algorithm is verified by a real case. © 2013 American Society of Civil Engineers.