Self-adaptive heuristic algorithm for solving ship traffic organization and scheduling problem

The invention provides a self-adaptive heuristic algorithm for solving a ship traffic organization and scheduling problem. The self-adaptive heuristic algorithm comprises the following steps: establishing a one-way channel ship traffic organization and scheduling mathematical model with the goal of minimizing the total time of entering and leaving a port of a ship; obtaining ship basic information, berth information and anchoring ground information of the comprehensive harbor district of the Huanggang; using an adaptive heuristic algorithm (AHA) to solve the model. In the AHA, the genetic algorithm is used as a basic optimization model, and Q-learning is utilized to adaptively adjust crossover and mutation operators matched with ship numbers and port entering and leaving directions in the iteration process. Considering that the algorithm may fall into a local optimal solution, the invention introduces a simulated annealing algorithm to perform annealing operation on part of excellent individuals after genetic operation. According to the method, on the premise that safety is guaranteed, the total time for the ships to enter and leave the port is remarkably shortened, the ship dispatching efficiency of the one-way navigation port is improved, meanwhile, a new tool is provided for port ship traffic organization and dispatching optimization, and the defects of an existing ship traffic organization optimization method are overcome.