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

Claim 4:
5. The method for the fully autonomous waterborne inter terminal transportation scheduling according to claim 1, wherein the step 3) comprises:
3.1) designing a neighborhood space of the current solution;
3.2) defining two matrices to store neighborhood search and iterative information; first, defining an n×n-dimensional matrix, where n≤nv, which stores optimal solution information obtained after neighborhood transformation between any two path pairs and a sequence number of the path pair, wherein the sequence number is a row sequence number of a defined second matrix; the second matrix stores neighborhood transformation information of the corresponding path pair, including ID of two path involved in the transformation, the number of tasks transformed in the two paths and the positions in the path;
3.3) defining a tabu table, wherein the tabu table comprises tabu objects and tabu lengths, the tabu objects are defined as a transportation task ID and a path ID, and the tabu length is positioned as a sum of a number of current iteration steps and a preset number of steps of tabu release, and when the number of iteration steps is less than the tabu length, the transportation tasks in the tabu objects cannot be inserted into the corresponding path, so as to avoid the iteration from falling into a loop;
3.4) in each iteration, selecting the neighborhood transformation with the most cost reduction; if the transformed cost value is smaller than the current recorded minimum cost value and the transformation is not in the tabu table, recording the cost value as the minimum cost value and updating the path; it is noted that each iteration only needs to update the matrix information corresponding to the path with neighborhood transformation in the matrix, rather than update the matrices of all paths;
3.5) repeating the above steps from 3.1) to 3.4) for iteration, and gradually improving the quality of the scheduling scheme to approximate optimum through continuous neighborhood change and path update; wherein the final scheduling scheme is the paths of all the wAGVs, including the sequence of terminal nodes to be visited, the corresponding visit time, staying time and the number of loaded and unloaded cargoes.