The complex diagnostic problems that the existing binary test diagnostic strategy optimization technology can’t solve the multi-value test and the test accuracy is low, the optimization strategy based on information entropy under multi-value test is proposed. The optimization method is analyzed from considering or non-considering false alarm and missed detection which may occur during the test. The simulation is verified on two different instance systems with different degrees of complexity, and the algorithm is compared with the AO* algorithm. The results show that the method has the characteristics of not increasing the test cost and greatly reducing the test time. The result is in line with the theoretical expectation.