Treffer: Integrated optimisation of berth allocation and yard management in the parallel-layout automated container terminal under uncertainty.

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. [ABSTRACT FROM AUTHOR]

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