Aiming at the problems encountered by the traditional ant colony optimization in the time optimal path planning, the method of transforming the ant-cycle system model is studied. In the optimization process, it is coupled with the algorithm model by quantifying the node turning time, the pheromone update rule is adjusted accordingly, and the computational efficiency is taken into account. The improved mathematical model is simulated by MATLAB software, and the effectiveness of the improved ACO model is verified by comparing the optimization results of the standard map traveling salesman problem with the classical ant colony. The main variable parameters are selected, and the optimal combination is preliminarily screened out through the simulation analysis of their sensitivity to the results.
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