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To improve the stability of network data transmission and reduce the network consumption, the routing optimisation of computer network using ant colony optimisation (ACO) algorithm is studied in this article. A mathematical model of routing optimisation is introduced and analysed to explain possible approaches to improve the performance of traditional ACO algorithms. Our scheme introduces two factors: time delay and bandwidth to the heuristic function, reflecting the comprehensive information of each link to promote the comprehensiveness of ants in finding optimum solution. Then, the advanced strategy of state transition rule and pheromone updating rules are also proposed to raise the convergence speed of ACO. In simulations, we test relative factors including success rate, speed, and transmission delay of path finding. In the weighted connected graph with 20 points, the optimal path can be achieved using fewer iterations. In three standard network test data sets of MATLAB, the success rate gets 93.1%, 92.4% and 90.5% respectively. By the comparison of transmission delay and processing time, it also shows performance compared to classic ACO algorithms.