Container scheduling optimization strategy based on clustering algorithm in port logistics system

Aiming at some configuration and scheduling problems of automated guided vehicles (AGV), shore bridges and yard bridges in the loading and unloading operation process of container terminals in the port logistics system, the flow characteristics of containers between ships and yards are analyzed in detail in the light of operational characteristics. Considering the intersection of AGVs with shore bridges at the quay front and the intersection of AGVs with yard bridges in the yard area, a container truck scheduling optimization model based on the objective of minimizing the operation cost is designed. And adaptive particle swarm algorithm (APSO-C) is used to solve the three-dimensional scheduling model of container in port logistics system. The results show that the fastest arrival scheduling rule is basically better than the shortest distance scheduling rule, and with the increase of the container task volume, the gap between the two scheduling rule optimization objectives in the same situation is getting bigger and bigger. Compared with the shortest distance, the fastest arrival has a shorter total completion time, which is more in line with the actual terminal operation scheduling. In addition, as the number of shore bridges increases, the operation time gap between single-load AGV mode and multi-load AGV mode is proportional to the number of shore bridges. Obviously the APSO-C algorithm has better performance in the container scheduling optimization process, which is more in line with the actual operation requirements of the terminal.