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Urban traffic problem was an important factor that affects the development and restricts the economic construction of cities. It's a complex system in a random way so it was necessary to optimize traffic control signals to cope with so much urban traffic problems. A simulated annealing-particle swarm optimization (Sa-PSO) algorithm was developed which bases on particle swarm optimization (PSO) and metropol was rule. It effectively shows in dealing with the optimization of urban traffic signal timing. Simulation was carried out in a nine-intersection were a network and the result shows that the use of Sa-PSO method can reduce 41.0% of the average delay per vehicles, and 30.6% of the average stop rates comparing with fixed time plans.