Flexible yard space allocation plan for new type of automated container terminal equipped with unilateral-cantilever rail-mounted gantry cranes

Abstract

In this paper, new automated container terminals equipped with Unilateral-cantilever Rail-Mounted Gantry Cranes (URMGC) are considered as the research object. In the scenario, the automated guided vehicles can go deep among the container blocks arranged perpendicularly to the shoreline, which completely changes the yard’s operation mode and affects its operational efficiency. In addition, considering the shortage of storage space in the yard, a flexible space allocation strategy for these yards is studied, and a mixed integer quadratic programming model is established to minimize the horizontal transportation cost of containers. An improved particle swarm optimization algorithm is designed to compensate for the increased complexity of the proposed model. To accelerate the solution speed, the quantity and priority rules are developed to generate reasonable initial solutions, and two velocity updating strategies are adopted to accelerate convergence. Numerical experiments are conducted to validate effectiveness and efficiency of the proposed method, and comparisons with fixed space allocation strategy are presented. The results show that the strategy and solution adopted in this paper can reduce the driving distance of AGVs in such terminal configurations effectively and potentially increase the handling capacity of the yard.