Considering of reducing the cost of test and maintenance, a mathematical model with cost function as the objective function is established, which transforms the problem of Testability Index Allocation (TIA) in the process of avionics system upgrading and refitting into a Nonlinear Programming (NLP) problem.Aiming at this NLP, a hybrid optimization algorithm combining Particle Swarm Optimization (PSO) algorithm with Sequential Quadratic Programming (SQP) algorithm is used to solve the problem, which makes full use of the formers strong global search ability and the latters strong local accurate search ability, and supplies an optimal solution method for the TIA problem in the upgrading and refitting process of avionics system.The results show that, compared with using PSO and SQP alone, the hybrid algorithm can obtain the optimal value faster, which verifies the feasibility of the proposed allocation method.