Integrated optimisation of berth allocation and yard management in the parallel-layout automated container terminal under uncertainty
研究了在船舶信息不确定下，平行布局自动化集装箱码头中泊位分配、堆场空间分配和轨道吊调度的集成优化问题，构建了混合整数规划模型并用免疫变邻域搜索算法求解，为码头运营提供了管理启示。
To effectively address uncertainty in vessel information caused by adverse weather, epidemics, local conflicts, and maritime traffic accidents, this paper studies an integrated optimisation problem of berth allocation and yard management in automated container terminals (ACT). The study considers the parallel layout of ACTs and applies the dispersion-occupation rule for container storage to jointly optimise berth allocation, yard space allocation, and automatic rail-mounted gantry crane (ARMG) deployment. An uncertain mixed integer programming model is constructed to minimise the sum of automated transport robots (ARTs) transport costs, ARMG loading and unloading costs, and penalty costs during operations. The problem is solved using an immune variable neighbourhood search algorithm (IVNSA), which incorporates a correction strategy tailored to the problem's characteristics, as well as dividing and merging search operations. By comparing the experimental results of different algorithms across various scales, the solution quality advantage of IVNSA becomes more pronounced, thereby verifying the superiority of the proposed model and algorithm. Through sensitivity analysis, three management insights are proposed for terminal operations, aimed at effectively improving yard space utilisation and the efficiency of container pickups by ARMGs.