Global environmental pollution and climate warming are becoming more and more serious, and ports, as important hubs of transportation and key nodes of logistics system, have high carbon emissions. In this paper, based on the carbon peak carbon neutral goal, a green port intelligent platform is constructed, a green and lowcarbon oriented berth-shore-bridge allocation optimization model is designed, and a nested-loop solving algorithm is proposed. In terms of methodology, firstly, a green port intelligence platform with cloud architecture containing facility layer, data layer, service layer and application layer is constructed; then a berth-shore and bridge allocation coupling model is established with ship operation time as the coupling variable, and ship fuel consumption and carbon emission are embedded in the optimization objective; finally, a nested loop solving algorithm combining greedy algorithm and distributed hybrid genetic algorithm is designed. The simulation results show that the proposed nested loop algorithm has better convergence performance than NSGA-II and MNSGA-II, and the average running time is 22.1% lower than that of NSGA-II when solving the 24-ship scale problem; The multi-objective optimization model achieves a reduction of 31 kiloliters of carbon emissions by sacrificing 2.576 minutes of operation time; the 5G technology-enabled intelligent platform improves traffic density by 125 times, connection density by 20 times, and energy efficiency by 120 times compared with the traditional 4G platform. The study shows that the intelligent construction of green ports can effectively reduce carbon emissions, optimize resource allocation, improve port operation efficiency, and provide technical support and solutions for ports to achieve carbon peak carbon neutrality.
