Patent ID: 11886191
Assignee: ZHEJIANG UNIVERSITY
Field: Control (Instruments)
Classification: CPC G  B | IPC B  G

Claim 6:
7. A system for fully autonomous waterborne inter terminal transportation scheduling, comprising a waterborne autonomous guided vessel (wAGV) system, an initial path solving module of a dynamic scheduling model, an initial path construction module, a real-time optimization module and a scheduling module; wherein
the wAGV system comprises a number of wAGVs which are controlled by the scheduling module to execute transportation tasks;
the initial path solving module of the dynamic scheduling model is configured for acquiring parameters involved in defining the dynamic scheduling model, establishing the dynamic scheduling model, determining constraints of the model and acquiring a first initial scheduling path of the scheduling system, the parameters including waterway distance which is not a straight line Euclidean distance and waiting time;
the initial path construction module is configured for inserting new transportation tasks into the possible positions in all the existing wAGV paths according to the paths calculated in a previous step but has not been completely executed within a rolling horizon framework, calculating the insertion cost and selects paths and corresponding positions with the lowest insertion cost, selecting the paths and positions corresponding to the minimum cost, inserting the task into updated paths, and sequentially processing all new transportation tasks and obtaining updated initial paths;
the real-time optimization module is configured by adopting a heuristic algorithm based on tabu search, combining the initial paths obtained by the initial path construction module and constraints of the dynamic scheduling model to obtain a quasi-optimal scheduling result within the rolling horizon framework, and realizing the real-time scheduling system, the constraints including pickup followed by delivering and no transshipment; and
the scheduling module is configured for controlling, according to the scheduling result according to the paths of all wAGVs in the current rolling horizon step obtained by the real-time optimization module, the wAGVs to visit specific terminals at specific times according to the scheduling result according to the paths of all wAGVs in the current rolling horizon framework obtained by the real-time optimization module, picking up or unloading a specific number of containers, and completing the assigned transportation task in an approximately shortest driving path with the minimum waiting time and delay time.