Aiming at the problem that the traditional ant colony optimization(ACO) algorithm cannot solve the diagnosis strategy for multi-valued attribute systems(MVAS) accurately, based on the improvement of the ACO algorithm, the ANT clony optimization-test sequence(ANT-TS) algorithm is proposed to search the fault test sequence for MVAS. Firstly, multi-valued \emphD matrix and five-tuple are introduced to complete the formulation of the diagnosis strategy. Then, the ant colony algorithm is reformulated, where the state transition rule and initialization and update of pheromone for the algorithm are set to combine the diagnosis strategy of MVAS with the ANT-TS algorithm. Finally, the correctness and stability of the ANT-TS algorithm are verified by an example and stochastic simulation experiments. The experimental results show that the running process of the ANT-TS algorithm is the same as the fault diagnosis strategy of MVAS. The algorithm has fewer parameters, expected test cost and number of cycles, and run faster when comparing with the traditional ACO algorithm. The ANT-TS algorithm can obtain the test sequences with less expected test cost compared with the traditional algorithm such as the multi-valued Rollout algorithm and the multi-valued IG algorithm.