The systemonchip (SOC) contained a large amount of embedded memories, which were tested by a method of sharing builtin selftest circuits. The insertion process of the builtin selftest circuit was limited by the area overhead, test power and test time of the SOC. Aiming at this problem, the multimemory builtin selftest was modeled as a multiobjective optimization problem, and a multiobjective clustering genetic anneal algorithm was proposed. Based on the genetic algorithm, the algorithm obtained the memory compatible group through memory clustering, adopted the heuristic method to obtain the high quality initial solution, proposed an objective function with different weights under multiple constraints, and used the simulated annealing algorithm to evade better individuals to avoid local optimal solution risk. The results show that the proposed algorithm performs better than the genetic algorithm, and obtain memory solutions for testing, which reduces the power consumption by 113% or the test time by 487%, saving onchip test resources and test time.